Dissertations / Theses on the topic 'Hyperspectral imaging spectroscopy'

We have previously introduced a high throughput multiplexing computational spectral imaging device. The device measures scalar projections of pseudo-arbitrary spectral filters at each spatial pixel. This paper discusses simulation and initial experimental progress in performing computational spectral unmixing by taking advantage of the natural sparsity commonly found in the fractional abundances. The simulation results show a lower unmixing error compared to traditional spectral imaging devices. Initial experimental results demonstrate the ability to directly perform spectral unmixing with less error than multiplexing alone.

Electrical Engineering
M.S.E.E.
Hyperspectral imaging is an emerging technology in the field of biomedical engineering which may be used as a non-invasive modality to characterize tumors. In this thesis, a hyperspectral imaging system was used to characterize canine mammary tumors of unknown histopathology (pre-surgery) and correlate the results with the post-surgical histopathology results. The system consisted of a charge coupled device (CCD) camera, a liquid crystal tunable filter in the near infrared range (650-1100 nm), and a controller. Spectral signatures of malignant and benign canine mammary tumors were extracted and analyzed. The reflectance intensities of malignant tumor spectra were generally lower than benign tumor spectra over the wavelength range 650-1100nm. Previous studies have shown that cancerous tissues have a higher hemoglobin and water content, and lower lipid concentration with respect to benign tissues. The decreased reflectance intensity observed for malignant tumors is likely due to the increased microvasculature and, therefore, higher blood content of malignant tissue relative to benign tissue. Second derivative method was applied to the reflectance spectra. Peaks at 700, 840, 900 and 970 nm were observed in the second derivative reflectance spectra. These peaks were attributed to deoxy-hemoglobin, oxy-hemoglobin, lipid and water respectively. A Tissue Optical Index (TOI) was developed that enhances contrast between malignant and benign canine tumors. This index is based on the ratio of the reflectance intensity values corresponding to the wavelengths associated with the four chromophores. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) were also applied on the canine spectral dataset and the method was cross-validated. Preliminary results from 22 canine mammary tumors showed that the sensitivity and specificity of the PCA-LDA is method is 86% and 86% respectively. The sensitivity and specificity of the TOI model is 86% and 95% respectively. These results show promise in the non-invasive optical diagnosis of canine mammary cancer.
Temple University--Theses

Questo progetto di dottorato studia le differenti applicazioni delle tecniche ottiche non distruttive per la valutazione della qualità e della shelf-life di prodotti vegetali così come l’identificazione precoce di sviluppi microbici su superfici industriali. La spettroscopia, l’analisi dell’immagine e l’analisi dell’immagine iperspettrale possono giocare un ruolo importante nella valutazione sia della qualità che della sicurezza degli alimenti grazie alla rapidità e sensibilità della tecnica, specialmente quando si utilizzano strumenti semplificati portatili. Un approccio statistico multivariato (chemiometria) è richiesto al fine di estrarre informazioni dal segnale acquisito, riducendo la dimensionalità dei dati e mantenendo le informazioni spettrali più utili. Lo scopo del primo studio presentato – Testing of a Vis-NIR system for the monitoring of long-term apple storage – è la valutazione dell’applicabilità della spettroscopia nel visibile e vicino infrarosso (Vis-NIR) per il monitoraggio e la gestione delle mele durante lo stoccaggio a basse temperature. Per sette mesi è stata seguita l’evoluzione in termini di grado zuccherino e consistenza delle mele suddivise in classi di maturazione. I risultati hanno indicato che la spettroscopia è una tecnica non-distruttiva che consente una stima accurata dei parametri chimico-fisici per la classificazione delle mele in lotti omogenei. Il lavoro descritto nel secondo paragrafo - Wavelength selection with a view to a simplified handheld optical system to estimate grape ripeness – è finalizzato all’identificazione delle tre lunghezze d’onda più importanti per il riconoscimento, direttamente in campo, dell’uva pronta per essere raccolta al fine della messa a punto di un sistema semplificato e a basso costo. I coefficienti di regressione standardizzati del modello PLS (Partial Least Square) sono stati utilizzati per selezionare le variabili più importanti, che racchiudono l’informazione più utile lungo l’intero spettro. La stessa procedura è stata condotta per determinare la freschezza delle foglie di Valerianella durante la shelf-life - Selection of optimal wavelengths for decay detection in fresh-cut Valerianella Locusta laterr (terzo paragrafo). Lo scopo del lavoro presentato nel quarto paragrafo del primo capitolo - Comparison between FT-NIR and Micro-NIR in the evaluation of Acerola fruit quality, using PLS and SVM regression algorithms – è stimare l’acidità titolabile e il contenuto di acido ascorbico all’interno del frutto acerola, utilizzando uno strumento compatto e a basso costo denominato Micro-NIR, che lavora nell’intervallo spettrale 950-1650 nm. I dati spettrali sono stati modellati mediante l’applicazione di due algoritmi PLS e SVM (Support Vector Machine). La capacità predittiva dello strumento semplificato è risultata interessante per applicazioni di monitoraggio in campo, soprattutto modellizzando i dati in modo non lineare. Nel secondo capitolo, è presentata l’applicazione di immagini RGB per la valutazione delle superfici - Image texture analysis, a non-conventional technique for early detection of biofilm. La texture dell’immagine è definita come una differenza nella distribuzione spaziale, nella frequenza e nell’intensità dei livelli di grigio in ogni pixel dell’immagine. Questo metodo è stato determinante per l’identificazione precoce dello sviluppo microbico su superfici normalmente impiegate nell’industria alimentare. L’approccio chemiometrico è stato cruciale in ogni fase del progetto di dottorato ed è definito come un approccio statistico multivariato che si applica ai dati chimici per estrarre informazione utile, ridurre il rumore di fondo e l’informazione ridondante. Il lavoro presentato all’inizio del terzo capitolo - Hyperspectral image analysis: a tutorial - propone una procedura standard per l’elaborazione di dati tridimensionali, presentando un esempio relativo alla predizione del raffermamento del pane in cassetta. Il secondo paragrafo del terzo capitolo, presenta una applicazione dell’immagine iperspettrale su acerola, focalizzata sul contenuto di vitamina C - HSI for quality evaluation of vitamin C content in Acerola fruit. In questo lavoro, è stata acquisita l’immagine di dieci acerola, raccolte in funzione del livello di maturazione, definito in base al colore della buccia (cinque acerola verdi e cinque rosse). Lo spettro della polvere di vitamina C pura è stato utilizzato come riferimento per l’applicazione di due algoritmi di correlazione (spectral angle mapping e correlation coefficient), consentendo la costruzione di mappe qualitative di distribuzione dell’acido ascorbico all’interno del frutto. Lo scopo dell’ultimo lavoro presentato è la valutazione della qualità post raccolta dell’acerola - Selection of NIR wavelengths from hyperspectral imaging data for the quality evaluation of Acerola fruit. Le immagini iperspettrali di venti acerola sono state acquisite per cinque giorni consecutivi. La valutazione delle modificazioni spettrali durante il tempo ha consentito la selezione delle tre lunghezze d’onda caratterizzanti il processo di maturazione/degradazione del frutto. L’immagine in falsi colori, derivante dalla composizioni delle immagini alle tre lunghezze d’onda di interesse, consente l’identificazione precoce del processo degradativo in maniera rapida e non distruttiva. Le tre tecniche non distruttive impiegate in questo progetto di dottorato hanno dimostrato efficienza e applicabilità per la valutazione della qualità e della sicurezza degli alimenti, rispondendo alla necessità dell’industria alimentare di tecniche accurate, veloci e obiettive per assicurare produzioni ottimali lungo l’intero processo produttivo.
This PhD project regards different applications of non-destructive optical techniques to evaluate quality and shelf life of agro-food product as well as the early detection of biofilm on food plants. Spectroscopy, image analysis and hyperspectral imaging could play an important role in the assessment of both quality and safety of foods due to their rapidity and sensitivity especially when using simplified portable devices. Due to the huge amount of collected data, chemometric, a multivariate statistical approach, is required, in order to extract information from the acquired signals, reducing dimensionality of the data while retaining the most useful spectral information. The thesis is organized in four chapters, one for each technique and a final chapter including the overall conclusion. Each chapter is divided in case studies according to the matrix analysed and the data acquisition and elaboration carried out. The first chapter is about spectroscopy. The aim of the first study - Testing of a Vis-NIR system for the monitoring of long-term apple storage - is to evaluate the applicability of visible and near-infrared (Vis-NIR) spectroscopy to monitor and manage apples during long-term storage in a cold room. The evolution of the apple classes, originally created, was analysed during 7 months of storage by monitoring TSS and firmness. Vis-NIR allows an accurate estimation of chemical-physical parameters of apples allowing a non-destructive classification of apples in homogeneous lots and a better storage management. The work reported in the second paragraph - Wavelength selection with a view to a simplified handheld optical system to estimate grape ripeness - is aimed to identify the three most significant wavelengths able to discriminate grapes ready to be harvested directly in the field. Wavelengths selection was carried out with a view to construct a simplified handheld and low-cost optical device. Standardized regression coefficients of the PLS model were used to select the relevant variables, representing the most useful information of the full spectral region. The same approach was followed to discriminate freshness levels during shelf-life of fresh-cut Valerianella leaves - Selection of optimal wavelengths for decay detection in fresh-cut Valerianella Locusta Laterr. (third paragraph). The aim of the work presented in the fourth paragraph of the first chapter - Comparison between FT-NIR and Micro-NIR in the evaluation of Acerola fruit quality, using PLS and SVM regression algorithms - is to estimate titratable acidity and ascorbic acid content in acerola fruit, using a MicroNIR, an ultra-compact and low-cost device working between 950 – 1650 nm. The spectral data were modelled using two different regression algorithms, PLS (partial least square) and SVM (support vector machine). The prediction ability of Micro-NIR appears to be suitable for on field monitoring using non-linear regression modelling (i.e. SVM). In the second chapter, image analysis was performed. The traditional RGB imaging for the evaluation of image texture, a specific surface characteristic, is presented. The texture of an image is given by differences in the spatial distribution, in the frequency and in the intensity of the values of the grey levels of each pixel of the image. This technique was applied for the early detection of biofilm in its early stages of development, when it is still difficult to observe it by the naked eye, was evaluated (Image texture analysis, a non-conventional technique for early detection of biofilm). In the third paragraph, image and spectroscopy were combined in hyperspectral imaging applications. Data analysis by chemometric was crucial in any stage of my PhD project. Chemometric is a multivariate statistical approach that is applied on chemical data to extract the useful information avoiding noise and redundant data. At the beginning of the third chapter - Hyperspectral image analysis: a tutorial - proposes an original approach, developed as a flow sheet for three-dimensional data elaboration. The method was applied, as an example, to the prediction of bread staling during storage. The first application about hyperspectral on acerola is focused on the vitamin C content - HIS for quality evaluation of vitamin C content in Acerola fruit. Ten different acerola fruits picked up according to two different stages of maturity, based on the colour of the peel (5 green and 5 red acerola), were analysed. The spectra of pure vitamin C powder was used as references for computing models with two different correlation techniques: spectral angle mapping and correlation coefficient allowing the construction of a qualitative distribution map of ascorbic acid inside the fruit. The aim of the last one work presented is to evaluate acerola post-harvest quality - Selection of NIR wavelengths from hyperspectral imaging data for the quality evaluation of Acerola fruit. Hyperspectral images of 20 acerolas were acquired for five consecutive days and an investigation of time trends was carried out to highlight the most important three wavelengths that characterized the ripeness/degradation process of the Acerola fruit. The false-colour RGB images, derived from the composition of the three interesting wavelengths selected, data enable early detection of the senescence process in a rapid and non-destructive manner. In conclusion, the three non-destructive optical techniques applied in this PhD project have proved to be one of the most efficient and advanced tools for safety and quality evaluation in food industry answering the need for accurate, fast and objective food inspection methods to ensure safe production throughout the entire production process.

L’imagerie hyperspectrale proche infrarouge (PIR) permet d’obtenir une carte spectrale d’un échantillon organique. La mesure d’un spectre pour chaque pixel de la caméra permet notamment la recherche de composés minoritaires dans les poudres agroalimentaires. Cependant, l’analyse spectrale PIR est limitée à une couche de profondeur donnée. De plus, la taille des particules associée à une résolution insuffisante des caméras PIR actuelles induisent un mélange des signaux spectraux dans les pixels de l’image. Ces deux problèmes sont une limitation pour l’analyse des composés minoritaires dans les poudres agroalimentaires.Nous proposons une méthode permettant de déterminer la profondeur de détection d’une cible composite placée dans un produit pulvérulent tel que la farine de blé. Basée sur une régression par projection sur les structures latentes, cette méthode permet d’appréhender l’atténuation du signal PIR lorsque la couche de poudre augmente, et ce malgré les problèmes inhérents à la détection en profondeur.De plus, deux stratégies de démélange de spectres sont proposées dans le but de détecter les pixels contenant des signatures de particules minoritaires. Le manque de valeur de référence utilisées en tant que données de validation des algorithmes ainsi que l’ambiguïté des spectres des composés pures à démélanger sont deux difficultés majeures. Une première stratégie consiste à modélisation la variabilité des spectres étudiés via l’Analyse en Composantes Principales afin de construire un algorithme de détection performant. La deuxième stratégie, basée sur la Multivariate Curve Resolution Alternating Least-Squares permet le démélange des signaux par pixels dans un cas plus complexe
Near-infrared (NIR) hyperspectral imaging provides a spectral map for organic samples. Minor compounds in food powder can be looked for by analyzing the pixel spectra. However, the NIR spectral analysis is limited to a given depth. Besides, particles smaller than the pixel size induce a mixed spectral signature in the pixels. These two issues are an obstacle to the analysis of minor compounds in food powders.We propose a method to determine the detection depth of a composite target under a layer of powder such as wheat flour. It is based on the Partial Least Squares regression and provides an understanding of how the NIR signal is attenuated when the layer of powder despite the penetration depth issues.Two spectral unmixing strategies are proposed to detect pixel with minor compound NIR signatures. The lack of reference values to validate the model and the ambiguity of the spectral signature to unmix are two major difficulties. The first method models the spectral variability using Principal Component Analysis to design a performant detection algorithm. Then, for a more complex situation, the Multivariate Curve Resolution Alternating Least-Squares algorithm is used to unmix each pixel

La thèse propose une méthodologie d’analyse rapide basée sur l’étude de l’image hyperspectrale Raman d’un produit pharmaceutique falsifié sous forme solide afin, d’une part d’identifier les substances présentes, et d’autre part estimer la teneur du principe actif dans l’échantillon sans étalonnage préalable.La présence de produits pharmaceutiques falsifiés est un véritable enjeu de santé publique. Ce type de produits de santé est facilement disponible sur internet, et beaucoup d’exemples montrent leur dangerosité. De nombreuses techniques sont disponibles pour analyser ces produits et ainsi participer à la lutte contre la falsification de médicament. La combinaison de ces techniques analytiques permet une caractérisation approfondie de l’échantillon. Cependant, peu de techniques analytiques procurent l’ensemble des informations chimiques.L’imagerie chimique Raman est une technique qui répond aux exigences requises pour l’analyse de produits falsifiés sous forme solide. En effet, cette technique peu destructive permet de réutiliser l’échantillon pour des analyses complémentaires. L’imagerie chimique Raman combine les trois disciplines de spectroscopie Raman, microscopie et chimiométrie. Cette technique réalise des mesures successives de spectres Raman sur des zones adjacentes couvrant la surface de l’échantillon. Elle intègre donc des informations spatiales et spectrales. Les méthodes chimiométriques dites de résolution (MCR-ALS et DCLS) analysent le jeu de spectres pour extraire des informations qualitatives (détection des spectres purs du mélange) et des informations quantitatives (estimation de la concentration de la substance active). La méthodologie a été optimisée et validée avec des échantillons préparés en laboratoire, puis appliquée à des échantillons réels authentiques et falsifiés. La sensibilité de la méthode qualitative a été démontrée par la détection d’un principe actif antibiotique à la teneur de 0,3% m/m dans un comprimé à visée anabolisante. De plus la méthode a été capable de détecter les substances utilisées pour le traitement de dysfonctions sexuelles (sildénafil, tadalafil, vardénafil, dapoxétine). Malgré une forte émission de fluorescence, la méthode a réussi à discriminer les 3 sels de clopidogrel (hydrogénosulfate, bésilate et chlorhydrate). L’analyse quantitative directe sur des échantillons de Viagra® et de Plavix® a été jugée convenable avec une déviation de la teneur entre -15% et +24%. Cette déviation est considérée acceptable pour évaluer le risque sanitaire pour le patient et alerter les autorités de santé.Dans le cadre de l’analyse des produits falsifiés, il a été démontré que la micro-spectroscopie Raman associée aux méthodes chimiométriques permet de réaliser un « screening spectroscopique » des composants de l’échantillon, d’identifier les substances chimiques, de visualiser leur distribution sur la surface de l’échantillon et d’estimer leur teneur par « quantification directe »
The thesis proposes a rapid methodology of analysis based on the Raman hyperspectral image study of a solid form falsified pharmaceutical product in order to identify the substances in the sample and to estimate the content of the active ingredient in the sample without prior calibration.The presence of falsified pharmaceuticals is a real public health issue. This type of products is easily available on the internet, and many examples show their dangerousness. Many techniques are available for the analysis of these products and thus participate in the fight against drug falsification. The combination of these analytical techniques allows a comprehensive characterization of the sample. However few analytical techniques provide all the chemical information. Raman chemical imaging is a technique that meets the requirements for the analysis of falsified products in solid form. Indeed, this non-destructive technique makes it possible the reuse of the sample for additional testing. Raman chemical imaging combines the three disciplines of Raman spectroscopy, microscopy and chemometrics. This technique performs successive measurements of Raman spectra on adjacent location covering the surface of the sample. It therefore collects spatial and spectral information. The so-called resolution chemometric methods analyse the set of spectra in order to extract qualitative information (detection of pure spectra in the mixture) and quantitative information (estimate of the concentration of the chemical substance). The methodology was optimized and validated with samples prepared in the laboratory, and then applied to genuine and falsified real samples. The sensitivity of the qualitative method was demonstrated with the detection of an antibiotic active ingredient at a content of 0.3% m/m in an anabolic tablet. Moreover, the method was able to distinguish substances used for the treatment of sexual dysfunctions (sildenafil, tadalafil, vardenafil, dapoxetine). Despite a high fluorescence emission, the method successfully discriminated the 3 salts of clopidogrel (hydrogen sulfate, besylate and hydrochloride). Direct quantitative analysis of samples of Viagra® and Plavix® was found to be appropriate with a deviation between -15% and +24%. This deviation is considered acceptable to assess the health risk to the patient and to alert health authorities.For the analysis of falsified products, it has been demonstrated that Raman micro-spectroscopy combined with chemometric methods allows to perform a "spectroscopic screening" of the components in the sample, to identify chemical substances, to visualize their distribution on the sample surface and to estimate their content by "direct quantification"

L’imagerie hyperspectrale est désormais considérée comme un outil analytique à part entière dans l’industrie pharmaceutique, aussi bien au cours du développement pour assurer la qualité d’un produit que pour résoudre des problématiques de production après la mise sur le marché du médicament. Dans ces travaux, la microscopie Raman est utilisée pour étudier la distribution en principes actifs et excipients au sein d’une forme pharmaceutique solide, en se focalisant tout particulièrement sur l’identification d’un composé faiblement dosé. Ce dernier est défini comme étant un produit ayant de faibles contributions spatiale et spectrale, signifiant qu’il est distribué dans quelques pixels de l’image avec une information spectrale peu présente dans un spectre de mélange. Alors que la plupart des algorithmes chimiométriques se basent sur la décomposition de moments statistiques, nécessitant une variation suffisante entre les échantillons (les pixels d’une image), les limites de ces outils pour résoudre ce cas spécifique sont rapidement atteintes.La première partie de la thèse met en évidence les difficultés de détection d’un composé faiblement dosé en utilisant l’analyse en composantes indépendantes et la résolution multivariée de courbes. Des méthodologies de travail sont proposées pour contourner ces limitations. Pour les deux techniques, les étapes de réduction de dimensions apparaissent comme des paramètres critiques de la méthode. La seconde partie de la thèse se focalise sur l’espace des signaux pour déterminer des cartes d’absence/présence de constituants ou pour détecter des constituants dans une formulation inconnue, en se basant sur des espaces spectraux portant une information relative aux constituants de la formulation. Les techniques proposées sont parfaitement adaptées à la détection d’un composé faiblement dosé et ces méthodes pourraient être adaptées à d’autres techniques de mesure ou d’autres domaines d’application
Hyperspectral imaging is now considered as a powerful analytical tool in the pharmaceutical environment, both during development to ensure the drug product quality and to solve production issues on commercialized products.In this thesis, Raman microscopy is used to study the distribution of actives and excipients in a pharmaceutical drug product, by especially focusing on the identification of a low dose compound. This latter product is defined as a compound which has low spatial and spectra contributions, meaning that it is scattered in a few pixels of the image and that its spectral response is mixed with the other compounds of the formulation. While most chemometric tools are based on the decomposition of statistical moments (requiring sufficient variations between samples or image pixels), some limitations have been rapidly reached. The first part of this thesis highlights the difficulty to detect a low dose compound in a product by using independent component analysis or multivariate curve resolution. Different methodologies are proposed to circumvent these limitations. For both techniques, reduction of dimensions and filtering steps appears as critical parameters of the method. The second part of the thesis focusses on the signal space to determine absence/presence compound maps or to detect the compounds in an unknown formulation. The proposed methods are only based on the spectral space of each formulation compound. There are perfectly suitable to a low dose compound and should be well-adapted to other analytical techniques or to other environments

En combinant des techniques de microscopie et de spectroscopie, il est possible de réaliser des images résolues spectralement. Ces images apportent des réponses à de nombreux problèmes en chimie, biologie, et médecine. La diffusion Raman cohérente (CRS) s'est révélée capable de surpasser la diffusion Raman spontanée dans l'analyse chimique d'échantillons, en offrant une meilleure résolution spatiale et un temps d'acquisition plus faible. La vitesse d'acquisition de l'information spectrale demeure toutefois un facteur limitant en imagerie CRS, et de nombreuses recherches se concentrent sur le développement de nouvelles méthodes d'acquisition. Le présent travail s'inscrit dans cette démarche. En combinant la diffusion Raman stimulée (une branche de la CRS), la focalisation spectrale d'impulsions optiques, ainsi qu'une ligne à délai acousto-optique, nous réalisons les premières mesures à de telles vitesses d'acquisition. Le cadre théorique, technologique, ainsi que l’ingénierie nécessaire pour parvenir à ce résultat sont détaillés. Cette technique d'acquisition rapide est illustrée par le suivi de réaction chimique, le contrôle qualité pharmaceutique, en biologie, et en histologie
Combining microscopy and spectroscopy, one can achieve spectrally resolved imaging, and provide a solution to various chemical, biological, or medical challenges. Coherent Raman scattering (CRS) has proven extremely valuable in providing chemical information, with a higher resolution and shorter acquisition time than spontaneous Raman scattering. The acquisition rate of the spectral information from a sample remains the limiting factor of CRS imaging, and several experimental schemes are being investigated to push the technology toward higher imaging frame rates. This work develops one such scheme. Combining stimulated Raman scattering (a CRS technique), spectral focusing with chirped pulses, and a fast acousto-optic delay line, we achieved unprecedented spectral acquisition rates. The theoretical, technological, and engineering frameworks enabling such acquisition are described in details. The application to pharmaceutical quality control, time resolved chemical transformations, biology, and histology are demonstrated

L'évolution de l'environnement et le climat sont, actuellement, au centre de toutes les attentions. Les impacts de l'activité des sociétés actuelles et passées sur l'environnement sont notamment questionnés pour mieux anticiper les implications de nos activités sur le futur. Mieux décrire les environnements passés et leurs évolutions sont possibles grâce à l'étude de nombreux enregistreurs naturels (sédiments, spéléothèmes, cernes, coraux). Grâce à eux, il est possible de caractériser des évolutions bio-physico-chimiques à différentes résolutions temporelles et pour différentes périodes. La haute résolution entendue ici comme la résolution su sante pour l'étude de l'environnement en lien avec l'évolution des sociétés constitue le principal verrou de l'étude de ces archives naturelles notamment en raison de la capacité analytique des appareils qui ne peuvent que rarement voir des structures fines inframillimétriques. Ce travail est bâti autour de l'hypothèse que l'utilisation de caméras hyperspectrales (VNIR, SWIR, LIF) couplée à des méthodes statistiques pertinentes doivent permettre d'accéder aux informations spectrales et donc bio-physico-chimiques contenues dans ces archives naturelles à une résolution spatiale de quelques dizaines de micromètres et, donc, de proposer des méthodes pour atteindre la haute résolution temporelle (saisonnière). De plus, a n d'avoir des estimations ables, plusieurs capteurs d'imageries et de spectroscopies linéaires (XRF, TRES) sont utilisés avec leurs propres caractéristiques (résolutions, gammes spectrales, interactions atomiques/moléculaires). Ces méthodes analytiques sont utilisées pour la caractérisation de la surface des carottes sédimentaires. Ces analyses spectrales micrométriques sont mises en correspondance avec des analyses géochimiques millimétriques usuelles. Optimiser la complémentarité de toutes ces données, implique de développer des méthodes permettant de dépasser la difficulté inhérente au couplage de données considérées par essence dissimilaire (résolutions, décalages spatiaux, non-recouvrement spectral). Ainsi, quatre méthodes ont été développées. La première consiste à associer les méthodes hyperspectrales et usuelles pour la création de modèles prédictifs quantitatifs. La seconde permet le recalage spatial des différentes images hyperspectrales à la plus basse des résolutions. La troisième s'intéresse à la fusion de ces dernières à la plus haute des résolutions. Enfin, la dernière s'intéresse aux dépôts présents dans les sédiments (lamines, crues, tephras) pour ajouter une dimension temporelle à nos études. Grâce à l'ensemble de ces informations et méthodes, des modèles prédictifs multivariés ont été estimés pour l'étude de la matière organique, des paramètres texturaux et de la distribution granulométrique. Les dépôts laminés et instantanés au sein des échantillons ont été caractérisés. Ceci a permis d'estimer des chroniques de crues, ainsi que des variations biophysico-chimiques à l'échelle de la saison. L'imagerie hyperspectrale couplée à des méthodes d'analyse des données sont donc des outils performants pour l'étude des archives naturelles à des résolutions temporelles fines. L'approfondissement des approches proposées dans ces travaux permettra d'étudier de multiples archives pour caractériser des évolutions à l'échelle d'un ou de plusieurs bassin(s) versant(s)
The evolution of the environment and climate are, currently, the focus of all attention. The impacts of the activities of present and past societies on the environment are in particular questioned in order to better anticipate the implications of our current activities on the future. Better describing past environments and their evolutions are possible thanks to the study of many natural recorders (sediments, speleothems, tree rings, corals). Thanks to them, it is possible to characterize biological-physical-chemical evolutions at di erent temporal resolutions and for di erent periods. The high resolution understood here as the su cient resolution for the study of the environment in connection with the evolution of societies constitutes the main lock of the study of these natural archives in particular because of the analytical capacity devices that can only rarely see ne inframillimetre structures. This work is built on the assumption that the use of hyperspectral sensors (VNIR, SWIR, LIF) coupled with relevant statistical methods should allow access to the spectral and therefore biological-physical-chemical contained in these natural archives at a spatial resolution of a few tens of micrometers and, therefore, to propose methods to reach the high temporal resolution (season). Besides, to obtain reliable estimates, several imaging sensors and linear spectroscopy (XRF, TRES) are used with their own characteristics (resolutions, spectral ranges, atomic/molecular interactions). These analytical methods are used for surface characterization of sediment cores. These micrometric spectral analyses are mapped to usual millimeter geochemical analyses. Optimizing the complementarity of all these data involves developing methods to overcome the di culty inherent in coupling data considered essentially dissimilar (resolutions, spatial shifts, spectral non-recovery). Thus, four methods were developed. The rst consists in combining hyperspectral and usual methods for the creation of quantitative predictive models. The second allows the spatial registration of di erent hyperspectral images at the lowest resolution. The third focuses on their merging with the highest of the resolutions. Finally, the last one focuses on deposits in sediments (laminae, oods, tephras) to add a temporal dimension to our studies. Through all this information and methods, multivariate predictive models were estimated for the study of organic matter, textural parameters and particle size distribution. The laminated and instantaneous deposits within the samples were characterized. These made it possible to estimate oods chronicles, as well as biological-physical-chemical variations at the season scale. Hyperspectral imaging coupled with data analysis methods are therefore powerful tools for the study of natural archives at ne temporal resolutions. The further development of the approaches proposed in this work will make it possible to study multiple archives to characterize evolutions at the scale of one or more watershed(s)

The application of hyperspectral imaging technique in the wavelength range of 400-1000 nm to estimate some of the maturity parameters of mangoes was investigated. Mangoes with different quality levels were grouped using principle component analysis (PCA). Feature wavelengths were identified to predict total soluble solids content, water content and firmness using simple correlation, first derivative, partial least square (PLS) regression analysis and measured values. Calibration models were developed using the selected wavelengths from correlation coefficients, first derivative, partial least square (PLS) regression analysis and corresponding maturity parameters employing artificial neural network model to predict total soluble solids content, water content and firmness of the fruit. Performance of the models was compared using the correlation coefficient (r) values. Fruit firmness was predicted with high correlation coefficient (r=0.88) followed by water content (r=0.81) and total soluble solids (r=0.78) using wavelengths selected from simple correlation of first derivative data with the parameters and ANN model. The results of the study demonstrated the scope for further research on maturity and quality evaluation of fruits using hyperspectral imaging technique.

Boreal peatlands store carbon sequestered from the atmosphere over millennia and the importance of this and the other ecosystem services these areas provide is now widely recognised. However, a changing climate will affect these environments and, consequently, the services they provide to the global population. The rate and direction of environmental change to peatlands is currently unclear and they have not yet been included in many climate models. This may in part be due to the ecological heterogeneity and spatial extent of these areas and the sparse sampling survey methods currently adopted. Hyperspectral remote sensing from satellite platforms may in future offer an approach to surveying and do so at the high spectral and spatial resolutions necessary to infer ecological change in these peatlands. However, work is required to develop methods of analysis to determine if hyperspectral data can be used to measure the overstorey vegetation of these areas. This will require an understanding of how annual and inter-annual cyclical changes affect the peatland plant canopy reflectances that would be recorded by hyperspectral sensors and how these reflectances can be related to state variable of interest to climate scientists, ecologists and peatland managers. There are significant areas of peatland within Scotland and, as it is towards the southern extreme of the boreal peatlands, these may be an early indicator of environment change to the wider boreal region. Calluna vulgaris, a hardy dwarf shrub, is the dominant overstorey species over much of these peatlands and could serve as a proxy for ecological, and consequently, environmental change. However, little has been done to understand how variations in leaf pigments or canopy structural parameters influence the spectral reflectance of Calluna through annual and inter-annual growth and senescence cycles. Nor has much work been done to develop methods of analysis to enable images acquired by hyperspectral remote sensing to be utilised to monitor change to these Calluna dominated peatlands over time. To advance understanding of the optical properties of Calluna leaves and canopies and develop methods to analyse hyperspectral images laboratory, field and modelling studies have been carried out in time series over a number of years. The leaf and canopy parameters significantly affecting reflectance have been identified and quantified. Differences between published Chlorophyll(a+b) in vivo absorption spectra and those determined were found. Carotenoids and Anthocyanins were also identified and quantified. The absorption spectra of these pigments were incorporated into a canopy reflectance model and this was coupled to a Calluna growth model. This combined model enabled the reflectance of Calluna canopies to be modelled in daily increments through annual and inter-annual growth and senescence cycles. Reasonable results were achieved in spectral regions where reflectance changed systematically but only for homogeneous Calluna stands. However, it was noted during this research that the area of support for the spectral measurements appeared to differ from that assumed from the specification provided by the spectroradiometer manufacturers. The directional response functions (DRFs) of two spectroradiometers were investigated and wavelength, or wavelength region, specific spatial dependences were noted. The effect that the DRFs of the spectroradiometers would have on reflectances recorded from Calluna canopies was investigated through a modelling study. Errors and inaccuracies in the spectra that would be recorded from these canopies, and commonly used biochemical indices derived from them, have been quantified.

I ghiacciai montani sono importanti fonti di dati paleoclimatici, essenziali allo studio dei cambiamenti climatici e ambientali. L'aumento della fusione dei ghiacciai sta portando alla perdita di preziose informazioni utili a predire l’evoluzione del clima. In questo contesto, è fondamentale definire le linee guida e creare mappe per l’identificazione delle aree idonee ad essere perforate. Nel primo anno di dottorato, ho definito l’idoneità di un ghiacciaio alla perforazione (SICD) come la probabilità di estrarre un campione di ghiaccio che possiede una stratigrafia ben conservata, utile alla ricostruzione del clima del passato. Le varabili ambientali introdotte nel modello, relazionate con la perforabilità, sono state selezionate in accordo alle perforazioni già effettuate, e alla letteratura scientifica, considerando l’opinione degli esperti. Due modelli spaziali sono stati sviluppati: il promo basato sulla conoscenza di esperti, il secondo di tipo probabilistico. Le variabili scelte (pendenza, rilievo locale, temperatura, radiazione solare diretta) sono state così combinate al fine di mappare le aree potenzialmente perforabili presenti nelle Alpi e in Asia. L’accuratezza del modello è stata valutata e sono state indicati i siti più idonei ad essere perforati. La ricerca ha permesso di fornire preziose informazioni utili alla scelta dei prossimi siti di perforazione. Nel secondo anno di dottorato un Sistema Aeromobile a Pilotaggio Remoto (SAPR) è stato sviluppato per acquisire misure spettrali durante campagne di spettroscopia di campo. Il sistema, nominato HyUAV, è basato su una piattaforma APR equipaggiata con uno spettrometro e una camera RGB. HyUAV è in grado di acquisire simultaneamente dati iperspettrali (350-1000 nm, 1.5 nm di risoluzione spettrale) della radiazione riflessa dalla Terra e immagini RGB. Un’ottica specifica (EOR) è stata sviluppata al fine di ottimizzare il campo di vista dello spettrometro e di misurare il segnale di Durk Current durante il volo. Le performance geometriche, radiometriche e spettrali del sistema sono state caratterizzate attraverso alcuni test di laboratorio ed è stata valutata l’accuratezza e la precisione dei dati iperspettrali raccolti attraverso un test di volo. Due metodi per la stima della riflettanza da UAV sono stati proposti e discussi. I risultati raggiunti mostrano: i) un’ottima stabilità del sistema (in termini geometrici, radiometrici e spettrali); ii) misure spettrali accurate (sia in termini di radianza che di riflettanza); iii) risultati simili tra i due metodi di stima della riflettanza. Lo studio ha dimostrato che il sistema HyUAV può essere considerato affidabile al fine di supportare indagini di spettroscopia di campo e promettente per un'ampia gamma di applicazioni ambientali. La spettroscopia ad immagine è una tecnica efficace che fornisce importanti informazioni per la caratterizzazione delle proprietà ottica delle superfici a scala spaziale di dettaglio. Applicata all’analisi delle carote di ghiaccio, essa può essere considerata una tecnica innovativa utile a migliorare la conoscenza dei cambiamenti climatici. Durante il terzo anno di dottorato, ho sviluppato un sistema automatico per acquisire immagini iperspettrali (HYCE) in camera fredda. Il sistema è composto da una un motore lineare ad alta precisione spaziale, il quale trasporta uno spettrometro iperspettrale ad immagine (Headwall Photonics VINR, 380-1000 nm, 2-3 nm di risoluzione spettrale, 1004 pixels spaziali) e una lampada alogena dedicata. Test di laboratorio sono stati effettuati al fine di valutare le componenti del sistema. Le prime immagini iperspettrali di una carota di ghiaccio sono state acquisite in camera fredda ed analizzate. In particolare è stato calcolato lo Snow Darkening Index (SDI) ed è stata verificare la sua applicabilità per la stima delle concentrazione di deposizioni atmosferiche minerarie nelle carote di ghiaccio.
Mountain glaciers and non-polar ice cores are very detailed sources of paleo-proxy data essential to achieve a complete overview of climate and environmental change. The increase in the glaciers melting leads to a loss of information, affecting the possibility to predict the climate evolution. In this context, is important to define a set of guidelines and create dedicated maps to identify suitable glaciers for ice core drilling. In the first year of the research, the Suitability for Ice Core Drilling (SICD) was defined as the likelihood of drilling a glacier to retrieve an ice core with preserved stratigraphic information that allows the reconstruction of historical climate conditions. Environmental variables related to the SICD were selected on the basis of previously drilled sites, according to available scientific literature and on the base of glaciologists opinions. A quantitative Weight of Evidence method was implemented and key variables (slope, local relief, temperature and direct solar radiation) are combined to map the potential drilling sites in the European Alps and in the Asian High Mountain glaciers. Accuracy is evaluated and first indications of potential drilling sites are reviewed. Results are valuable for future selection of potential drilling sites of mountain glacier. In the second year of the PhD, a light UAV for collecting spectral measurements was developed in support of field spectroscopy surveys. The system, namely HyUAV, is based on a four-rotors platform with hovering capability, equipped with a non-imaging spectrometer and a RGB camera. The HyUAV collects simultaneously hyperspectral data (350-1000 nm, ~1.5 nm spectral resolution) of Earth reflected radiance and RGB images. The Entrance Optics Receptor (EOR) was specifically developed to optimize the spectrometer field of view and to collect in-flight dark current. The geometric, radiometric and spectral performances of the system were characterized through dedicated laboratory tests. Then, the accuracy of the hyperspectral data were evaluated during flight tests, comparing spectral data collected from HyUAV with ground-based measurements. Two methods to estimate surface reflectance from HyUAV were investigated and discussed, with the aim of providing further suggestions for an accurate retrieval of surface reflectance. The results achieved shown: i) good systems stability of the system (in terms of geometric, radiometric and spectral features); ii) accurate spectra measurements (in terms of radiance and reflectance); iii) similar results for the delineated methods to calculate reflectance. The HyUAV demonstrated to be a reliability systems for supporting field spectroscopy surveys and a promising platform for a wide range of environmental applications. Imaging spectroscopy is a powerful technique that provides insights information, with the aim to investigate spectral features, related to surfaces properties and materials composition, at very detailed spatial resolution. Applied to ice cores analysis hyperspectral imaging, it can be considered an innovative technique, that could provide valuable information improving the understanding of climate change. During the third year of PhD, a fully automated Hyperspectral systems for Imaging Ice core (HyIICE) was developed in a cold-room environment. The HyIICE is composed by an high-precision linear stage, which embeds a imaging hyperspectral sensor (Headwall Photonics VINR spectrometer, 380-1000 nm, 2-3 nm spectral resolution, 1004 spatial pixels) and a dedicated stable halogen light source. Several tests were performed on the system to evaluate the components and verify the efficiency in cold environments. First hyperspectral imaging of ice cores were collected in order to inspecting the potential of hyperspectral imaging for the quantitative estimation of parameters related to past atmospheric and climate conditions.

Im Rahmen dieser Arbeit wird ein Konzept entwickelt und umgesetzt, welches eine umfassende Bewertung von Daten flugzeuggetragener hyperspektraler Systeme ermöglicht. Es baut auf mehreren aktuellen Initiativen zur Erfassung der Datenqualität flugzeuggetragener Sensoren auf: Der ''European Facility for Airborne Reseach'', der ''Quality Assessment for Earth Observation Workgroup'' und dem ''Joint Committee for Guides in Metrology''. Bei der Befliegung eines Gebietes mit hyperspektralen Sensorsystemen werden mehrere, teilweise sich überlappende, Flugstreifen aufgenommen. Es wird vorgeschlagen, die Bildinformationen dieser Überlappungsbereiche als redundant anzusehen und so die innere Variabilität der Daten zu erfassen. Die jeweils zwischen zwei Flugstreifen auftretende Variabilität kann (aufgrund unterschiedlicher Blickrichtungen) als ungünstigster anzunehmender Fall (''worst-case'') betrachtet werden und ergänzt daher existierende Ansätze, die sich auf die Auswertung homogener Flächen konzentrieren. Das entwickelte Konzept ist auf unterschiedliche Sensorsysteme anwendbar, somit generisch und kann problemlos in die aktuelle Datenprozessierungskette des Deutschen Zentrums für Luft- und Raumfahrt e.V. integriert werden. Im ersten Abschnitt der Arbeit wird dargelegt, wie korrespondierende Pixelpaare, die in den jeweiligen Streifen an gleicher Geolokation liegen, ermittelt werden können. Darauf aufbauend erfolgt eine Plausibilitätsüberprüfung der erfaßten Pixelpaare unter Verwendung von Zuverlässigkeitsmetriken, die auf Basis höherwertigerer Datenprodukte berechnet werden. In einem weiteren Schritt werden die Ergebnisse genutzt, um die notwendigen Parameter für eine optimierte Bildauswertung - hier im Sinne der Zuverlässigkeit - abzuleiten. Abschließend werden die Pixelpaare benutzt, um die globale Variabilität der Reflektanzwerte abzuschätzen. Insgesamt werden durch diese Arbeit die existierenden Methoden zur Qualitätskontrolle optischer Bilddaten umfassend ergänzt.
This work proposes a methodology for performing a quality assessment on the complete airborne hyperspectral system, thus ranging from data acquisition up to land-product generation. It is compliant with other quality assessment initiatives, such as the European Facility for Airborne Research (EUFAR), the Quality Assessment for Earth observation work-group (QA4EO) and the Joint Committee for Guides in Metrology (JCGM). These are extended into a generic framework allowing for a flexible but reliable quality assessment strategy. Since airborne hyperspectral imagery is usually acquired in several partially overlapping flight-lines, it is proposed to use this information redundancy to retrieve the imagery''s internal variability. The underlying method is generic and can be easily introduced in the German Aerospace Center DLR''s hyperspectral processing chain. The comparison of two overlapping flight-lines is not straightforward, should it only be because the presence of geo-location errors present in the data. A first step consists in retrieving the relative variability of the pixel''s geo-locations, hence providing pairs of pixels imaging the same areas. Subsequently, these pairs of pixels are used to obtain quality indicators accounting for the reproducibility of mapping-products, thus extending the EUFAR''s quality layers up to land-products. The third stage of the analysis consists of using these reliability results to improve the mapping-products: it is proposed to maximise the reliability over the mapping-methods'' parameters. Finally, the repeatability assessment is back propagated to the hyperspectral data itself. As a result, an estimator of the reflectance variability (including model-, and scene-induced uncertainties) is proposed by means of a blind-deconvolution approach. Altogether, this complements and extends the EUFAR quality layers with estimates of the data and products repeatability while providing confidence intervals as recommended by JCGM and QA4EO.

This degree project focused on examining new possible application of near-infrared (NIR) spectroscopy for quantitative and qualitative characterization of refuse derived fuel (RDF). Particularly, two possible applications were examined as part of the project. Firstly, use of NIR hyperspectral imaging for classification of common materials present in RDF. The classification was studied on artificial mixtures of materials commonly present in municipal solid waste and RDF. Data from hyperspectral camera was used as an input for machine learning models to train them, validate them, and test them. Three classification machine learning models were used in the project; partial least-square discriminant analysis (PLS-DA), support vector machine (SVM), and radial basis neural network (RBNN). Best results for classifying the materials into 11 distinct classes were reached for SVM (accuracy 94%), even though its high computational cost makes it not very suitable for real-time deployment. Second best result was reached for RBNN (91%) and the lowest accuracy was recorded for PLS-DA model (88%). On the other hand, the PLS-DA model was the fastest, being 10 times faster than the RBNN and 100 times faster than the SVM. NIR spectroscopy was concluded as a suitable method for identification of most common materials in RDF mix, except for incombustible materials like glass, metals, or ceramics. The second part of the project uncovered a potential in using NIR spectroscopy for identification of inorganic chlorine content in RDF. Experiments were performed on samples of textile impregnated with a water solution of kitchen salt representing NaCl as inorganic chlorine source. Results showed that contents of 0.2-1 wt.% of salt can be identified in absorbance spectra of the samples. Limitation appeared to be water content of the examined samples, as with too large amount of water in the sample, the influence of salt on NIR absorbance spectrum of water was too small to be recognized.
FUDIPO

The aim of this thesis is to study and evaluate the application of hyperspectral image analysis as a non-destructive analysis method for historical mortars. This method was applied on 35 sampled mortars in varying sizes and type from the inner walls of the fortified medieval city Carcassonne. By using near infrared spectroscopy and classifying the complex multivariate data by applying the SIMCA method (Soft Independent Modelling of Class Analogies) it is possible to conduct an in depth analysis of the samples. This can then further our understanding about the construction phases as well as construction techniques used as indicated through the chemometric analysis that can identify and group the mortars in accordance to raw material and transformation process. From this could four distinct groups be found in the PCA models, two Roman periods and two high medieval periods, allowing to study Carcassonne prior to and after its enclosure. A find from the first Roman period indicates on a bathhouse or public building existing prior to the construction of the defensive wall, leading to the hypothesis that maybe more parts of the inner wall might contain older structures like this. The application of hyperspectral image analysis on historical mortars has proven itself a useful tool and simple method for studying mortars.
Målet med denna uppsats var att studera och evaluera applikationen av hyperspektral bildanalys som en icke-destruktiv analysmetod på historiskt murbruk. Instrumentet applicerades på 35 murbruksprover i varierande storlek och typ tagna från de inre murarna av den befästa medeltida staden Carcassonne. Med nära infraröd spektroskopi och klassificering av den multivariata genom SIMCA metoden (Soft Independent Modelling of Class Analogies) var det möjligt att göra en djupgående analys av proverna. Detta tillvägagångssätt kan då främja vår förståelse om stadens konstruktionsfaser och konstruktionstekniker som indikeras genom den chemometriska analysen som kan identifiera murbruket utefter råmaterial samt hur murbruket tillverkats. Från dessa metoder kunde fyra distinkta grupper finnas i PCA modellerna, två romerska perioder och två högmedeltida perioder, vilket öppnade för tolkning både innan och efter stadsmurarna rests. Ett fynd från den första romerska perioden indikerar på förekomsten av ett badhus eller publik byggnad vars väggar sedan återanvänts vid konstruktionen av den inre stadsmuren. Detta fynd leder till hypotesen att potentiellt andra delar av den inre stadsmuren kan innehålla väggar från äldre byggnader som denna. Applikationen av hyperspektral bildanalys på historiskt murbruk har påvisat sig ett användbart verktyg och simpel metod för att studera murbruk.

Lors de leur formation il y a 4,6 milliards d’années, les comètes ont intégré des matériaux transformés selon les conditions physiques et dynamiques du disque d’accrétion mais aussi une part de composés issus du milieu interstellaire. Parce qu’elles ont préservé leurs propriétés, étudier les comètes permet de mieux comprendre les conditions régnant dans le disque proto-planétaire entourant le jeune Soleil à une époque qui nous est inaccessible. Cela permet également de comprendre les différentes populations de comètes, leur processus de formation, leurs évolutions dynamiques, leur activité lorsqu’elles s’approchent du Soleil ou encore leur structure.La sonde européenne Rosetta a accompagné la comète 67P/Churyumov-Gerasimenko pendant deux ans. À son bord, une dizaine d’instruments ont permis d’étudier l’évolution de son activité, les gaz, la morphologie de surface ou les poussières parmi d’autres objectifs. VIRTIS est le spectromètre visible-infrarouge de Rosetta. Sa composante d’imagerie spectrale, VIRTIS-M, permet d’avoir accès à la dimension spatiale tout en bénéficiant d’une résolution spectrale modérée tandis que VIRTIS-H est un spectromètre ponctuel bénéficiant d’une plus grande résolution spectrale. Mon travail a reposé sur le traitement et l’analyse des données de ces instruments et se découpe en deux parties concentrées sur l’étude de la surface du noyau.La première est une analyse des paramètres spectraux et photométriques : albédo, pente spectrale, direction principale de la diffusion de la lumière par les particules, rugosité macroscopique. Dans une étude globale, j’ai mis en évidence les variations spatiales de certains de ces paramètres ; comparé les résultats issus de différents modèles ainsi que des deux instruments. J’ai ensuite déterminé localement ces paramètres, soulignant des différences selon le type de terrains ciblé. Ces études permettent de mieux comprendre les mécanismes liés à l’activité (dépôt/soulèvement de poussières, altération spatiale, variations de la teneur en glace) ou aux variations des propriétés de la surface (composition, texture).Le deuxième enjeu de cette thèse était de reproduire en laboratoire les observations réalisées par VIRTIS, et ce afin d’apporter des contraintes sur la composition et la texture de la surface. En collaboration avec l’IPAG de Grenoble j’ai donc mené des expériences consistant à produire des poudres très fines constituées de matériaux similaires à ceux que l’on suspecte d’être présents sur le noyau de 67P : matière organique (imitée par un charbon), silicates (olivine) et sulfures de fer (pyrite et pyrrhotite) sont ainsi tous observés dans les comètes ou leurs analogues. Je les ai ici broyés à des échelles micrométriques à nanométriques puis j’ai réalisé des mesures en réflectance dans la même gamme spectrale que VIRTIS. J’ai pu ainsi étudier les effets provoqués par les variations de la taille des grains, de la composition ou de la texture du mélange, mettant en avant des combinaisons reproduisant le spectre moyen de la comète. De manière générale, cette étude permet de mieux comprendre l’influence de matériaux rarement étudiés comme les sulfures de fer ainsi que le comportement spectral de poudres dont la taille des grains atteint un ordre de grandeur proche de celle de la longueur d’onde, ce qui est primordial dans l’étude des surfaces cométaires
During the Solar System formation, 4.6 billion years ago, comets accreted materials which have been transformed according to the physical and dynamical conditions of the accretion disk but also a part of components coming from the interstellar medium. By preserving a primordial composition, the study of comets allows us to better understand the conditions of the proto-planetary disk surrounding the young Sun of an epoch which is now inaccessible. Moreover, it consists also to understand the various comets populations, their formation process, dynamical and activity evolution as they inward and outward the Sun or their structure.The ESA/Rosetta mission followed the comet 67P/Churyumov-Gerasimenko during two years. A ten of instruments has been dedicated to the study of the evolution of its activity, gas release, surface morphology, dust and other objectives. VIRTIS is a visible/infrared spectrometer instrument. It is composed of VIRTIS-M, an imaging spectrometer which gives access to spatial information with moderate spectral resolution and VIRTIS-H, a point spectrometer with a higher spectral resolution. This study is based on the data analysis of VIRTIS instruments and is divided into two parts focused on the study of the nucleus surface.The first part is an analysis of the spectral and photometric parameters: albedo, spectral slope, the main direction of the light diffusion by particles, macroscopic roughness. In a global study, I highlighted the spatial variations of albedo and spectral slope; compared results derived from different models as well as from both instruments. Then, I determined these parameters locally, revealing differences between two types of terrains. This approach allows to better understand the mechanisms linked to the activity (dust drop-off/uprising, space weathering, ice content variation) and also to the surface properties (composition, texture).The second goal of the thesis is to reproduce in the laboratory the observations realized by VIRTIS to give constraints on the composition and texture of the surface. In collaboration with IPAG (Grenoble, France) I led experiments consisting of the production of very fine powders made of materials which look like those we suspect to be present on the nucleus of 67P: organic matter (mimicked by a coal), silicates (olivine) and iron sulfides (pyrite and pyrrhotite) are all observed on comets or their analogues. I ground them to micrometric to nanometric scales and I realized reflectance measurements in the same spectral range than VIRTIS. Then, I have been able to observe effects caused by the variations of the grain size, composition or texture of the mixture and to highlight combinations reproducing the mean comet VIRTIS spectrum. Finally, this work enables us understanding the influence of material poorly studied such as iron sulfides as well as the spectral behaviour of powders composed of grain sizes reaching an order of magnitude close to the wavelengths, which is essential in the study of cometary surfaces

Oberflächennahe Prozesse werden durch die dynamischen Eigenschaften der Bodenoberfläche besonders beeinflusst. Zwar sind die kausalen Zusammenhänge dieser Prozesse weitestgehend bekannt, doch gibt es einen Mangel an verfügbaren Datenquellen und Erhebungsmethoden, die es erlauben, die Prozesse auf unterschiedlichen Skalen zu quantifizieren. Das Ziel dieser Arbeit bestand darin, das Potential ausgewählter moderner Fernerkundungstechnologien zu bewerten, relevante Bodeneigenschaften zu quantifizieren und damit das Verständnis von oberflächennahen Prozessen in degradierten Landschaften zu verbessern. Das Studiengebiet befand sich in einer Rekultivierunglandschaft des Niederlausitzer Braunkohletagebaus Welzow-Süd. Die Größe von 4 ha ermöglichte eine umfassende, interdisziplinäre und multi-temporale Analyse der Bodeneigenschaften auf Grundlage von Fernerkundungsmethoden sowie hydrologischen und bodenkundlichen Feld- und Labormessungen. Die Quantifizierung der Bodenfeuchte als eine entscheidende Variable für Infiltrations- und Abflussprozesse war das Ziel von labor- und feldspektroskopischen Messungen sowie von hyperspektralen Flugzeugscanner-Messungen. Der hierbei entwickelte Normalized Soil Moisture Index (NSMI) wurde als optimales Quantifizierungsmodell für Oberflächen-Bodenfeuchte im Feld ermittelt. Bodenrauhigkeit wurde in hoher Präzision durch Anwendung eines stationären Laserscanners gemessen und in Form neuartiger multi-skalarer Indizes quantifiziert. Die Analyse der raum-zeitlichen Verteilungen ermöglichte die Identifizierung von Rauhigkeitsmustern, die unter dem Einfluss der Erosion im Feld entstanden. Diese Arbeit entwickelte neuartige Methoden und Indizes zur Quantifizierung von Oberflächen-Bodenfeuchte und Rauhigkeit im Feld. Für die Zukunft verspricht deren Anwendung die Entwicklung eines tieferen Verständnisses von Bodenerosionsprozessen sowie die Sammlung wertvoller Daten durch Monitoring- und Modellierungskampagnen.
Soil processes taking place in the context of erosion and land degradation are highly dependent on the properties of the surface. While the causes and effects of such processes are commonly well understood on a conceptual level, there is a lack of adequate data sources allowing for their quantification at various spatial scales. The main goal of this thesis was to assess the role of state-of-the-art remote sensing methods for the quantification of soil properties with the aim to improve the understanding of surface processes taking place in a degraded landscape. The chosen study area of 4 ha size located in a lignite mine in eastern Germany allowed for a comprehensive, interdisciplinary and multi-temporal analysis of surface properties based on remote sensing, pedological and hydrological measurements. The quantification of surface soil moisture as an important variable for infiltration and runoff processes has been the objective in laboratory and field spectroscopic experiments as well as in airborne hyperspectral measurements. The newly developed Normalized Soil Moisture Index (NSMI) was identified as the most robust quantifier for surface soil moisture in the field. Surface roughness was successfully quantified at high precision in form of novel multiscale indices derived from datasets collected with a stationary laser scanning device. The analysis of spatiotemporal roughness distributions allowed for the detection of distinct patterns that developed under the influence of soil erosion in the field. The thesis developed a set of methods and indices that successfully implement the quantification of surface soil moisture and roughness in the field. For the future, the application of these methods promises further insights into the details of soil erosion processes taking place as well as the collection of invaluable datasets to be used for soil erosion monitoring and modeling campaigns.

La Tomographie Optique Diffuse (TOD) est désormais une modalité d’imagerie médicale fonctionnelle reconnue. L’une des applications les plus répandues de cette technique est celle de l’imagerie fonctionnelle cérébrale chez l’Homme. En effet, cette technique présente de nombreux avantages, notamment grâce à la richesse des contrastes optiques accessibles. Néanmoins, certains verrous subsistent et freinent le développement de son utilisation, spécialement pour des applications chez l’Homme adulte en clinique ou dans des conditions particulières comme lors du suivi de l’activité sportive. En effet, le signal optique mesuré contient des informations venant de différentes profondeurs de la tête, et donc de différents types de tissus comme la peau ou le cerveau. Or, la réponse d’intérêt étant celle du cerveau, la réponse de la peau peut dégrader l’information recherchée. Dans ce contexte, ces travaux portent sur le développement d’un nouvel instrument de TOD permettant d’acquérir les dimensions spatiale, spectrale et de temps de vol du photon de façon simultanée, et ce à haute fréquence d’acquisition. Au cours de cette thèse, l’instrument a été développé et caractérisé sur fantôme optique. Ensuite, il a été validé in-vivo chez l’Homme adulte, notamment en détectant l’activité du cortex préfrontal en réponse à une tâche de calcul simple. Les informations multidimensionnelles acquises par notre système ont permis d’améliorer la séparation des contributions des différents tissus (Peau/Cerveau). Elles ont également permis de différencier la signature de la réponse physiologique de ces tissus, notamment en permettant de détecter les variations de concentration en Cytochrome-c-oxydase. Parallèlement à ce développement instrumental, des simulations Monte-Carlo de la propagation de la lumière dans un modèle anatomique de tête ont été effectuées. Ces simulations ont permis de mieux comprendre la propagation de la lumière dans les tissus en fonction de la longueur d’onde et de valider la pertinence de cette approche multidimensionnelle. Les perspectives de ces travaux de thèse se dirigent vers l’utilisation de cet instrument pour le suivi de la réponse du cerveau chez l’Homme adulte lors de différentes sollicitations comme des stimulations de TDCS, ou en réponse à une activité sportive
The Diffuse Optical Tomography (DOT) is now a relevant tool for the functional medical imaging. One of the most widespread application of this technic is the imaging of the human brain function. Indeed, this technic has numerous advantages, especially the richness of the optical contrast accessible. Nevertheless, some drawbacks are curbing the use of the technic, especially for applications on adults in clinics or in particular environment like in the monitoring of sports activity. Indeed, the measured signal contains information coming from different depths of the head, so it contains different tissues types like skin and brain. Yet, the response of interest is the one of the brain, and the one of the skin is blurring it. In this context, this work is about the development of a new instrument of DOT capable of acquiring spatial and spectral information, as well as the arrival time of photons simultaneously and at a high acquisition speed. During the PhD thesis the instrument has been developed and characterised on optical phantoms. Then, it has been validated in-vivo on adults, especially by detecting the cortical activation of the prefrontal cortex, in response to a simple calculation task. Multidimensional information acquired by our system allowed us to better distinguish between superficial and deep layers. It also allowed us to distinguish between the physiological signature of those tissues, and especially to detect the variations of concentration in Cytochrom-c-oxydase. Concurrently to this experimental work, Monte-Carlo simulation of light propagation in a model off a human head has been done. Those simulations allowed us to better understand the light propagation in tissues as function as their wavelength, and to validate the relevance of our multidimensional approach. Perspectives of this work is to use the developed instrument to monitor the brain’s response of the Human adult to several solicitations like tDCS stimulation, or sports activity

Thesis (MSc Food Sc)--Stellenbosch University, 2012.
ENGLISH ABSTRACT: Hectolitre mass (HLM) measurements allow rapid and accurate determination of grain density. HLM devices from different countries (Australia, Canada, France, Germany, South Africa, the United Kingdom and the United States of America [USA]) have been investigated for their effect on the HLM measurements of oats. In addition, the potential of near infrared (NIR) hyperspectral imaging has been evaluated to distinguish between oat samples with different HLM values. Comparing HLM measurements obtained from the respective devices, the USA and the South African devices resulted in significantly (P<0.05) lower HLM values compared to the other devices where as the German device resulted in higher values (P<0.05) than the other devices. HLM values from all the devices were highly correlated with intra-class correlation (ICC) consistency values of at least 0.90. These high correlations would allow direct replacement of the South African device with any of the other devices. The equipment selected as replacement should ideally be calibrated according to the ISO 7971-3 standard (i.e. the device currently used in Germany). HLM values significantly (P<0.05) increased when oat samples were rubbed before measurements were made, indicating the importance of continuation of this sample preparation step. The investigation on the effect of the operator on HLM determinations showed that the unskilled operator measured HLM values significantly different to those obtained by the skilled operator. This emphasises the importance of training in spite of HLM measurements being a simple procedure. A poor correlation (r = 0.18) was found between protein content and HLM values of oat samples. Moisture content significantly affected the HLM values of oats and results clearly showed a decrease in HLM values with increasing moisture content. Scanning electron microscope (SEM) micrographs revealed that the starch granules became swollen and that they increased in size with an increase in moisture content, resulting in a decrease in HLM. NIR hyperspectral imaging offers the testing of individual grains non-destructively. This is often required by plant breeders because they subsequently need to plant selected grains. NIR offers this option to plant breeders. NIR hyperspectral imaging, which combines NIR spectroscopy with digital imaging, was used to distinguish between six oat samples with varying HLM values. NIR spectroscopic differences were observed between the images of the two samples with the highest and lowest HLM values (60.2 and 49.35 kg.hL-1). Less distinct differences were observed in the NIR hyperspectral images of two samples differing by less than 2.0 kg.hL-1. Although mixed oat samples were used, these preliminary results established the possible use of NIR hyperspectral imaging in evaluating oat samples from breeding trials. The use of this technique could also be extended to evaluation of other quality characteristics of oats.
AFRIKAANSE OPSOMMING: Hektolitermassa- (HLM-)metings maak snelle en akkurate bepaling van korreldigtheid moontlik. HLM-toestelle van verskillende lande (Australië, Kanada, Frankryk, Duitsland, Suid-Afrika, die Verenigde Koninkryk en die Verenigde State van Amerika) is ondersoek vir hulle uitwerking op die HLM-metings van hawer. Daarby is die potensiaal van nabyinfrarooi- (NIR-)hiperspektrale beelding geëvalueer om tussen hawermonsters met verskillende HLM-waardes te onderskei. Tydens vergelyking van HLM-metings verkry van die onderskeie toestelle, het die Amerikaanse en die Suid-Afrikaanse toestelle beduidend (P<0.05) laer HLM-waardes opgelewer in vergelyking met die ander toestelle terwyl die Duitse toestel hoër waardes (P<0.05) as die ander toestelle getoon het. Daar was hoë korrelasies tussen die HLM waardes verkry van die apparate met intraklaskorrelasie (IKK) konsekwentheidwaardes van ten minste 0.90. Hierdie hoë korrelasies sou direkte vervanging van die Suid-Afrikaanse toestel met enige van die ander toestelle moontlik maak. Die toerusting gekies as vervanging sou ideaal gesproke in ooreenstemming met die ISO 7971-3 standaard gekalibreer kon word (bv. die toestel wat tans in Duitsland gebruik word). HLM-waardes het beduidend (P<0.05) verhoog toe hawermonsters gevryf is voor metings gemaak is, wat dui op die belang van verlengde gebruik van hierdie stap tydens die voorbereiding van monsters. Die ondersoek na die uitwerking van die operateur op HLM-bepalings het getoon dat die onervare operateur HLM-waardes beduidend verskillend gemeet het teenoor dié verkry deur die ervare operateur. Dit beklemtoon die belang van opleiding ten spyte daarvan dat HLM-metings ’n eenvoudige prosedure is. ’n Swak korrelasie (r = 0.18) is aangetref tussen proteïeninhoud en HLM-waardes van hawermonsters. Voginhoud het die HLM-waardes van hawer beduidend beïnvloed en resultate het duidelik ’n styging in HLM-waardes met verhoging van die voginhoud getoon. Aftaselektronmikroskoop- (AEM-)mikrobeelde het aangedui dat die styselgranules swel en in grootte toeneem met verhoging van die voginhoud, wat aanleiding gee tot ’n verlaging in HLM. NIR-hiperspektrale beelding maak die toets van individuele korrels op niedestruktiewe wyse moontlik. Dit word dikwels deur plantkwekers vereis aangesien hulle na toetsing uitgesoekte korrels moet plant. Nabyinfrarooi bied hierdie opsie aan plantkwekers. NIR-hiperspektrale beelding, wat NIRspektroskopie met digitale beelding kombineer, is gebruik om te onderskei tussen ses hawermonsters met wisselende HLM-waardes. NIR-spektroskopiese verskille tussen die beelde van die twee monsters met die hoogste en laagste HLM-waardes (60.2 en 49.35 kg.hL-1) is waargeneem. Minder duidelike verskille is in die NIR-hiperspektrale beelde van twee monsters wat met minder as 2.0 kg.hL-1 verskil het, waargeneem. Alhoewel gemengde hawermonsters gebruik is, het hierdie voorlopige resultate die moontlike gebruik van NIR-hiperspektrale beelding by die evaluering van hawermonsters van kweekproewe vasgestel. Die gebruik van hierdie tegniek sou ook uitgebrei kon word tot die evaluering van ander kwaliteitseienskappe van hawer.

The food industry needs to comply with more strict rules (from regulatory agencies) and meet customers’ demands for higher quality. Emerging technologies for quality and safety inspection are becoming fundamental and needful to fulfil these purposes. The optical techniques have been using in different fields (agriculture, food, chemistry etc.). During harvest, post-harvest and food processing these techniques are well applied to predict crucial quality parameters. Spectra of intact food samples can be measured in few seconds without any sample preparation and expert personnel trained. Compared to this technology, chemical techniques are time-consuming, require sample preparation and use of chemical reagents which are often not sustainable for the environment. This PhD project regards different applications of non-destructive optical techniques to evaluate the quality of agri-food products as well as the development of customized optical devices to fulfil the needs of agri-food chain which is going toward a concept of industry 4.0. This thesis starts with a focus on optical sensing in terms of concept, data management and general applications in agri-food chains highlighting the attitude to be a green technology. Then, in two chapters were set the stage for models' development using commercial benchtop and portable optical devices to enhance the advantages of this technique in terms of performance (compared to other analytical instruments) and versatility in coffee industry and in the olive supply chain. Moreover, thanks to the need of the winemaking industry to improve the production of high-quality wines, another chapter was developed to show the latest frontiers in terms of data collection for maturation control of wine grapes. Therefore, optical hand-held and stand-alone prototypes were designed, built, and tested in order to shift the current paradigm of grape maturation monitoring (based on lab analysis) with a new one that allows a low-cost non-destructive real-time monitoring providing information with temporal and spatial resolution. Finally, a last chapter has been introduced as an initial step for future developments in the field of hyperspectral imaging sensors. Therefore, a cost-effective hyperspectral device was developed to drastically reduce the cost of these instruments comparing it with those present on the market. To clarify, for these instruments the cost limitations are not strictly related to the device itself but for the specific applications. Indeed, even though the hyperspectral imaging technique can collect a large amount of data, the application of only one device (in some cases) is not enough to cover all the critical points the industry has to face. The production process in a firm or the monitoring in field require distributed systems to collect data and provide information. In these circumstances, considering the application of several hyperspectral devices, the costs become prohibitive for the majority of the companies and the research is going toward the development of hyperspectral sensors taking into account a considerable cost reduction. To conclude, this PhD project has proved advantages and frontiers of optical sensing as one of the most efficient and advanced tools for safety and quality evaluation in the food industry throughout the entire production process.

Avec l’émergence des nouveaux aciers chargés en éléments réactifs, la caractérisation des états de surface a pris une nouvelle dimension. En effet, différentes familles d’oxyde sont dommageables pour la qualité de surface de l’acier et peuvent nuire à l’application de revêtements annexes. Aussi, afin d’assurer une bonne qualité aux produits finis, le besoin de caractériser, en ligne, la surface de l’acier sur toute sa largeur est de plus en plus nécessaire. L’imagerie hyperspectrale est une technologie en plein essor qui permet à la fois la caractérisation spatiale et spectrale d’une surface. Elle n’avait cependant encore jamais été employée pour la caractérisation de couche mince dans l’industrie sidérurgique. Durant ma thèse, deux méthodologies ont ainsi été développées pour répondre à ce besoin: l’une via une mesure en réflexion spéculaire et l’autre via une mesure en émission. En complément d’un travail de synthèse d’échantillons de référence, un développement expérimental complet allant d’un banc de simulation aux traitements des données a été réalisé. Ce travail a permis de démontrer la capabilité de l’imagerie hyperspectrale pour la détection de couche mince d’oxyde sur un acier parfois à plusieurs centaines de degrés Celsius. Ces résultats encourageants ont conduit à réaliser la première implantation industrielle de cette technologie. Ce travail de thèse a permis d’étudier théoriquement et expérimentalement les phénomènes mis en jeu et de passer du concept répondant à un besoin industriel à l’implémentation en ligne d’un capteur dédié à la caractérisation d’une couche mince d’oxyde sur une surface en défilement dans des conditions industrielles
With the emergence of new steel loaded in reactive elements, the characterization of the physico-chemical properties of the surface states has taken a new dimension. Indeed, the thin films of oxide formed are damaging for the surface quality of the steel and may adversely affect the application of varied coatings. Also, to ensure a good quality on finished products, the need to characterize, online, the steel surface over its entire width is increasingly necessary. The hyperspectral imaging is an emerging technology that allows both spatial and spectral characterization of a surface. It had never been used to characterize thin layers in the steel industry. During my PhD, both methodologies have been developed to meet this need: one via a measurement in specular reflection and the other via a measurement in emission. In addition to a synthesis of reference samples, a full experimental development ranging from a simulation bench to the data processing was performed. This work has demonstrated the capability of the hyperspectral imaging to detect thin surface oxide layers on a steel surface, sometimes at several hundred degrees Celsius. These encouraging results led to the first industrial implementation of this technology. This thesis made it possible to study theoretically and experimentally the phenomena involved and to move from the concept that meets an industrial need to the implementation of an online sensor dedicated to the characterization of a thin oxide layer on a moving surface in industrial conditions

Les ukiyo-e désignent les estampes produites au Japon entre le XVIIe et le XIXe siècle. Elles sont le reflet des changements sociaux et économiques de la société japonaise pendant la période d’Edo (1615-1868), ère de paix et de prospérité, et adoptent une nouvelle iconographie représentant des scènes de la vie quotidienne et des plaisirs de la vie. Les techniques et les matériaux employés par les artistes évoluent également. Les premières estampes colorées apparaissent au début du XVIIIe siècle et au XIXe siècle, avec l’ouverture économique du Japon, des pigments chimiques importés d’Occident enrichissent la palette chromatique disponible. La collection Torralba (Musée de Saragosse, Espagne) comprend un fonds d’estampes ukiyo-e représentatives du XVIIIe et XIXe siècle. L’accès à ce corpus nous donne l’opportunité d’étudier les matériaux utilisés grâce à des méthodes adaptées, non invasives et sans contact, afin de suivre l’évolution de la technique et/ou des matériaux (locaux ou importés) employés. Un développement méthodologique est impératif afin d’analyser et de caractériser ces matériaux (pigments, colorants, liants, support), notamment les colorants organiques, difficiles à identifier. Les techniques de spectroscopie de réflectance dans l’infrarouge et d’imagerie hyperspectrale sont théoriquement capables de discriminer les matériaux organiques et inorganiques. Cependant les œuvres analysées sont souvent des systèmes complexes et les données obtenues sont la plupart du temps difficiles à interpréter de manière certaine. Il est donc indispensable de mettre en place une stratégie multi analytique afin de croiser les données et d’obtenir un maximum d’informations pour permettre l’identification des matériaux. L’étude de l’évolution des matériaux au cours du temps permet ainsi d’obtenir des informations importantes du point de vue de l’histoire de l’art et des techniques, reflets notamment des évolutions culturelles et sociétales au Japon au cours du XIXe siècle
Ukiyo-e means the prints produced in Japan between the 17th and 19th centuries. They reflect the social and economic changes in Japanese society during the Edo period (1615-1868), era of peace and prosperity, and adopt a new iconography depicting scenes of everyday life and the pleasures of life. The techniques and materials used by artists are also changing. The first coloured prints appear in the early 18th century. From the 19th century, with Japan's economic opening, chemical pigments imported from the West enrich the available color palette. The Federico Torralba Collection (Museum of Zaragoza, Spain) includes ukiyo-e prints representative of the 18th and 19th centuries. Access to this corpus gives us the opportunity to study the materials used, through appropriate non-invasive and contactless methods, and to follow the evolution of technologies and/or materials (local or imported) used. A methodological development is imperative to analyse and characterise these materials (pigments, dyes, binders), including organic dyes which are difficult to identify. Reflectance spectroscopy techniques in the infrared (FORS) and Hyperspectral Imaging (HSI) are theoretically capable of distinguishing organic from inorganic materials. However, the analysed works are often complex systems and the data obtained are difficult to interpret with certainty for the most of the time. It is therefore essential to establish a multianalytical strategy to cross the data in order to get maximum information allowing the identification of materials. The study of the evolution of materials over time gives the opportunity to obtain important information in art history and history of technology, reflecting the cultural and societal evolution in 19th century Japan

Les imatges hiperespectrals són una mesura instrumental singular i de gran interès, ja que proporcionen informació química (espectral) i de distribució espacial (imatge) dels constituents de les mostres. Aquest fet les fa especialment interessants en aplicacions de la indústria farmacèutica, dels camps mediambiental i biomèdic i en la recerca i identificació de materials. L’objectiu d’aquesta tesi ha estat el coneixement de la naturalesa de la mesura de les imatges hiperespectrals amb la finalitat de dissenyar o adaptar eines d’anàlisi de dades més específiques i de proporcionar protocols d’actuació per a la interpretació d’aquest tipus de mesura en funció del tipus de tècnica espectroscòpica utilitzada i del problema químic d’interès. De manera específica, aquest treball s’ha centrat en l’estudi del potencial del mètode de resolució multivariant de corbes per mínims quadrats alternats, MCR-ALS, per a l’anàlisi d’imatges hiperespectrals, que proporciona mapes de distribució i espectres purs dels constituents de les imatges a partir únicament del coneixement de la mesura original. S’ha treballat amb l’anàlisi d’imatges individuals i l’anàlisi conjunta d’imatges obtingudes amb la mateixa tècnica o amb diferents plataformes espectroscòpiques. A partir de l’estudi d’imatges Raman i IR associades a problemes químics de diferents tipologies, s’han proposat protocols d’anàlisi que inclouen el preprocessat de les dades originals, l’obtenció dels mapes de distribució i espectres purs dels constituents de la imatge i el postprocessat dels mapes i espectres resolts per a l’obtenció d’informació addicional. L’ús dels mapes i espectres resolts proporciona informació molt diversa, com és ara la identificació, la quantificació i la caracterització de l’heterogeneïtat dels constituents de la imatge o la interpretació global i local d’un procés. Els mapes resolts han estat també una informació de partida excel·lent en altres tipus d’anàlisi, com la segmentació de la imatge o en procediments de superresolució, orientats a millorar la resolució espacial de les imatges instrumentals. La combinació de l’anàlisi multiconjunt de resolució i segmentació s’ha revelat de gran utilitat per a distingir poblacions de mostres de teixits biològics amb diferents estats patològics. Per últim, s’ha proposat un procediment per a la fusió i anàlisi d’imatges adquirides amb diferents tècniques espectroscòpiques i de diferent resolució espacial mitjançant una nova variant del mètode MCR-ALS per a estructures multiconjunt incompletes, que permet aprofitar la informació complementària de les tècniques acoblades i preservar la màxima resolució espacial.
Hyperspectral images are unique instrumental measurements that contain chemical (spectral) information and detailed knowledge of the distribution of the sample constituents on the sample surface scanned. This thesis is mainly oriented to know in depth the nature of this instrumental measurement in order to design and adapt specific chemometric tools that help in the proposal of general protocols for the interpretation of hyperspectral images according to the spectroscopic technique used and the chemical problem of interest. Particularly, much work has been focused on the study of the potential of multivariate curve resolution-alternating least squares, MCR-ALS, for the analysis of hyperspectral images. This algorithm provides distribution maps and pure spectra for the image constituents from the sole information contained in the raw measurement. Within this framework, individual analysis of images and image multiset analysis on data structures formed by images collected with the same technique or by images coming from different spectroscopic platforms have been explored. From the study of Raman and IR hyperspectral images linked to different chemical problem typologies, data analysis protocols have been proposed that include preprocessing of original data, recovery of distribution maps and pure spectra of image constituents and postprocessing of resolved maps and pure spectra to obtain further information. Resolved distribution maps and pure spectra provide diverse information, such as identification, quantification and heterogeneity characterization of the image constituents or the global and local description of a process. The use of resolved distribution maps has proven to be an excellent starting point for other kinds of analysis, such as image segmentation or super-resolution algorithms, oriented to improve the spatial resolution of experimental hyperspectral images. Combined multiset resolution and segmentation analysis has been shown to be very useful for the differentiation of populations of biological tissues with different pathological conditions. Finally, a strategy for data fusion of hyperspectral images from different spectroscopic platforms and different spatial resolution has been proposed. This approach uses a new variant of MCR-ALS for incomplete multiset structures that takes advantage of the complementary information provided by the different spectroscopic techniques without losing spatial resolution.

Background Tarkett AB Ronneby (Sweden) is a flooring solutions company, recognized for the manufacturing and recycling of homogeneous plastic flooring. Tarkett AB recycles mainly installation spill and manufacturing defects. However, Tarkett AB is considering widening its recycling capabilities to include old and torn plastic floors which may contain impurities and banned substances or plastic floors of competing brands. To accomplish this, Tarkett is considering a completely new recycling line with an automated sorting process instead of the current manual process. Thus, Tarkett proposes a dissertation to conceptualize a new automated sorting system with added capacity and increased functionality. Purpose This work aims to investigate the current sorting process and introduce conceptual solutions for a new automated sorting process capable of identifying and separating plastic floors according to the manufacturer, type, condition, and external waste by using existing technology. Method The methods and tools used in this work are mainly based on a modified product development process. Starting with data collection of the current sorting process, performing a need-finding, and extracting requirements for an automated sorting process, investigating relevant technology, evaluating technology based on scientific literature and tests. The testing was conducted in collaboration with two companies. Near-infrared scanners were tested with Holger AB, while pattern recognition systems were tested with Vision-Geek. Finally, three concepts for the automated sorting process were developed and shown through flow charts and 2D-3D illustrations. Results The results of this work showed that it was possible to use near-infrared and pattern recognition for the separation of plastic floors. Besides, three conceptual solutions for an automated sorting process were generated and showcased with schematic graphs and 2D-3D illustrations. The concepts describe how the sorting process functions and what technology is used for each step of the process. Concept 1 and Concept 2 used both pattern recognition and spectroscopy methods. While Concept 3 only used spectroscopy methods. Moreover, spectroscopy methods were used to sort plastic floors by content while pattern recognition by appearance. Conclusions Recycling of torn and old plastic flooring can be beneficial for both the environment and the recycling industry. Yet, it presents some challenges relating to reliable, fast, and nondestructive identification for sorting and separation purposes. New and proven technology such as near-infrared hyperspectral imaging and pattern recognition can be used. However, high-quality pattern and spectrum libraries of multiple plastic floors have to be created for optimal and reliable reference models. Furthermore, pattern recognition and near-infrared methods need to be tested further at an industrial scale.
Bakgrund Tarkett AB Ronneby (Sverige) är ett golvlösning företag, erkänt för tillverkning och återvinning av homogent plastgolv. Tarkett AB återvinner huvudsakligen installations spill och tillverkningsfel. Tarkett AB överväger dock att utvidga sina återvinnings förmågor till att omfatta gamla och sönderrivna plastgolv som kan innehålla föroreningar och förbjudna ämnen eller plastgolv från konkurrerande varumärken. För att åstadkomma detta överväger Tarkett en helt ny återvinnings linje med en automatiserad sorteringsprocess istället för den aktuella manuella processen. Således föreslår Tarkett ett examensarbete för att konceptualisera ett nytt automatiserat sorteringssystem med ökad kapacitet och ökad funktionalitet. Syfte Detta arbete syftar till att undersöka den nuvarande sorterings processen och introducera konceptuella lösningar för en ny automatiserad sorteringsprocess som kan identifiera och separera plastgolv efter tillverkare, typ, skick och externt avfall med befintlig teknik. Metod De metoder och verktyg som används i detta arbete är huvudsakligen baserade på en modifierad produktutvecklingsprocess. Vilket börja med datainsamling av den aktuella sorterings processen, hitta behov och extrahera krav för en automatiserad sorteringsprocess, undersöka relevant teknik, utvärdera tekniken baserad på vetenskaplig litteratur och tester. Testningen genomfördes i samarbete med två företag. Nära-infraröda skannrar testades med Holger AB, medan mönsterigenkänning system testades med Vision-Geek. Slutligen utvecklades tre koncept för den automatiserade sorterings processen och visades genom flödesscheman och 2D-3D-illustrationer. Resultat Resultaten av detta arbete visade att det var möjligt att använda nära-infraröd och mönsterigenkänning för separering av plastgolv. Dessutom genererades tre konceptuella lösningar för en automatiserad sorteringsprocess och visades med schematiska grafer och 2D-3D-illustrationer. Begreppen beskriver hur sorterings processen fungerar och vilken teknik som används för varje steg i processen. Koncept 1 och Koncept 2 använde både mönsterigenkänning och spektroskopi metoder. Medan Koncept 3 bara använde spektroskopi metoder. Spektroskopi metoderna användes för att sortera plastgolv efter innehåll medan mönsterigenkänning efter utseende. Slutsats Återvinning av sönderrivna plastgolv kan vara fördelaktigt för både miljön och återvinningsindustrin. Dock finns det några utmaningar med anknytning till pålitlig, snabb och icke-förstörande identifiering för sorterings- och separation ändamål. Ny och beprövad teknik som nästan infraröd hyperspektral avbildning och mönsterigenkänning kan användas. Emellertid måste mönster- och spektrum bibliotek av hög kvalitet av flera plastgolv skapas för optimala och pålitliga referens-modeller. Dessutom måste mönsterigenkänning och nära-infraröda metoder testas vidare i industriell skala.

Near-infrared spectroscopy (NIRS), Raman spectroscopy, and hyperspectral (HS) sensors were trialled in the present thesis. The four experimental chapters were conducted to investigate potential applications in the meat industries. The first study compared a handheld NIRS sensor connected to a smartphone (NIRvascan) against a benchtop NIRS sensor to measure chemical composition (pH, moisture, fat, protein) of beef and lamb in three different sample presentations (fresh intact, freeze-dried, and freeze-dried-oven-dried). Both sensors showed similar, moderate precision in predicting fat concentration on processed meat (r2 = 0.78–0.81, RPD = 2.1–2.3). However, the predictions on fresh intact meat were insufficient for even rough screening in the industry (r2 < 0.67, RPD < 2.0). The second study compared the NIRvascan sensor against a Raman spectrometer to differentiate grass-fed from grain-fed retail beef cuts. The NIRvascan was more accurate than the Raman when scanning lean tissue, whereas the Raman was more accurate on fat tissue (both >90% accuracy). This study showed NIRvascan to be cheaper and more practical for industry and consumer use compared to larger and more expensive instruments. The third study used a multi-sensory platform containing two HS sensors (visible – VIS: 400–900 nm, and short-wave infrared – SWIR: 900–1700 nm) to classify beef and sheep organs by organ type (heart, kidney, liver, or lung). Hearts and livers were the more accurately identified (accuracy >90%) than kidneys and lungs (50–70%). The fourth study used the same multi-sensory platform to identify sheep organs rejected or fit for human consumption. Hearts and livers were more accurately (78–96%) discriminated as diseased or healthy compared to kidneys and lungs (60–91%). In the latter two chapters, the SWIR and VIS HS sensors achieved similar accuracy although VIS was slightly more accurate in differentiating organ type and SWIR was slightly more accurate in differentiating organs rejected or not for human consumption. In conclusion, three of the four chapters showed the potential of novel spectroscopic sensors for applications in the meat industries and encouraged further studies with larger sample sizes. Furthermore, the multi-sensory platform showed excellent potential as it is non-contact and can run at chain speed.

L'imagerie hyperspectrale est maintenant très développée dans les applications de télédétection. Il y a principalement deux manières de construire les imageurs associés : la première méthode utilise un réseau et une fente, et l'image spectrale est acquise ligne par la ligne le long de la trajectoire du porteur. La seconde est basée sur le principe de la spectrométrie par transformée de Fourier (TF). Certains des systèmes utilisés sont construits de manière à enregistrer l'interférogramme de chaque point de la scène suivant le déplacement dans le champ. Le spectre de la lumière venant d'un point de la scène est alors calculé par la transformée de Fourier de son interférogramme. Les imageurs classiques basés sur des réseaux sont plus simples à réaliser et les données qu'ils fournissent sont souvent plus faciles à interpréter. Cependant, les spectro-imageurs par TF fournissent un meilleur rapport signal sur bruit si la source principale de bruit vient du détecteur.Dans la première partie de cette thèse, nous étudions l'influence de différents types de bruit sur les architectures classiques et TF afin d'identifier les conditions dans lesquelles ces dernières présentent un avantage. Nous étudions en particulier l'influence des bruits de détecteur, de photons, des fluctuations de gain et d'offset du détecteur et des propriétés de corrélation spatiale des fluctuations d'intensité du spectre mesuré. Dans la seconde partie, nous présentions la conception, la réalisation et les premiers résultats d'un imageur basé sur un interféromètre de Michelson à dièdres statique nommé DéSIIR (Démonstrateur de Spectro-Imagerie Infrarouge). Les premiers résultats montrent, qu'en mode spectromètre simultané, DéSIIR permet la restitution du spectre avec les spécifications requises dans le cadre des applications recherchées, c'est-à-dire détecter avec une résolution d environ 25 cm-1 un object de quelques degrés plus chaud que le fond de la scène et présentant une signature spectrale entre 3 et 5 juin. En mode spectromètre imageur, après recalage des images, il est possible de reconstruire le spectre de chaque point de la scène observée.

Total soluble solids (TSS) is a reliable indicator of melon eating quality, with a minimum standard of 10% recommended. The state of Australian melon production with respect to this quality criterion was considered within seasons, between growing districts and over seasons. It was concluded that improvement in agronomic practice and varietal selection is required to produce sweeter melons. The scientific literature addressing melon physiology and agronomy was summarised, as a background to the work that is required to improve melon production practices in Australia. The effect of source sink manipulation was assessed for commercially grown and glasshouse grown melon plants. The timing of fruit thinning, pollination scheduling, the application of a growth inhibitor and source biomass removal were assessed in relation to fruit growth and sugar accumulation. Results are interpreted against a model in which fruit rapidly increase in weight until about two weeks before harvest, with sugar accumulation continuing as fruit growth ceases. Thus treatment response is very dependant on timing of application. For example, fruit thinning at 25 days before harvest resulted in further fruit set and increased fruit weight but did not impact on fruit TSS (at 9.8%, control 9.3%), while thinning at 5 days before harvest resulted in a significant (Pless than 0.05) increase in fruit TSS (to 10.8%, control 9.3%) and no increase in fruit weight or number. A cost/ benefit analysis is presented, allowing an estimation of the increase in sale price required to sustain the implementation of fruit thinning. The effect of irrigation scheduling was also considered with respect to increasing melon yield and quality. To date, recommended practice has been to cause an irrigation deficit close to fruit harvest, with the intent of 'drying out' or 'stressing' the plant, to 'bring on' maturity and increase sugar accumulation. Irrigation trials showed that keeping plants stress-free close to harvest and during harvest, facilitated the production of sweeter fruit. The maintenance of a TSS grade standard using either batch based (destructive) sampling or (non-invasive) grading of individual fruit is discussed. On-line grading of individual fruit is possible using near infrared spectroscopy (NIR), but the applicability of the technique to melons has received little published attention. Tissue sampling strategy was optimised, in relation to the optical geometry used (in commercial operation in Australia), both in terms of the diameter and depth of sampled tissue. NIR calibration model performance was superior when based on the TSS of outer, rather than inner mesocarp tissue. However the linear relationship between outer and middle tissue TSS was strong (r2 = 0.8) in immature fruit, though less related in maturing fruit (r2 = 0.5). The effect of fruit storage (maturation/senescence) on calibration model performance was assessed. There was a negligible effect of fruit cold storage on calibration performance. Currently, the agronomist lacks a cost-effective tool to rapidly assess fruit TSS in the field. Design parameters for such a tool were established, and several optical front ends compared for rapid, though invasive, analysis. Further, for visualisation of the spatial distribution of tissue TSS within a melon fruit, a two-dimensional, or hyper-spectral NIR imaging system based on a low cost 8-bit charge coupled device (CCD) camera and filter arrangement, was designed and characterised.

Les récentes avancées dans le domaine des plates-formes d’instrumentation légères telles que les drones ou les nano-satellites ont fortement augmenté la demande de capteurs compacts, y compris les capteurs d’imagerie hyperspectrale infrarouge qui sont utilisés, de nos jours, dans des nombreuses applications militaires et civiles. Nous proposons une nouvelle caméra hyperspectrale compacte infrarouge dont les performances nous permettront de viser les domaines applicatifs tels que la détection de gaz (panaches volcaniques ou industriels), la détection de véhicules militaires, la surveillance d’ouvrages (barrages, pipelines) ou encore l’agriculture. Pour y arriver, nous avons choisi la spectro-imagerie par transformée de Fourier utilisant un interféromètre biréfringent à décalage latéral. Nous avons ensuite procédé à une modélisation approfondie de tels interféromètres afin de déterminer une configuration optimale associant compacité et résolution spectrale requise. Cette modélisation a été utilisée pour dimensionner trois prototypes avec des spécifications précises : deux prototypes dans le moyen infrarouge, l’un entièrement refroidi et l’autre partiellement refroidi et un prototype dans le lointain infrarouge. Nous avons ensuite réalisé le prototype partiellement refroidi que nous avons caractérisé en laboratoire et que nous avons mis en œuvre sur le terrain. Cette campagne de mesures nous a permis d’obtenir des images hyperspectrales dans des conditions réelles d’utilisation. Par l’analyse de ces images, nous avons évalué les performances opérationnelles de notre système et identifié les points à améliorer
Recent advances in the field of lightweight technical platforms like UAV or nano-satellite have increased the demand for compact sensors including infrared hyperspectral cameras which are used nowadays in number of military and civilian applications. We propose a new compact infrared hyperspectral camera, the performance of which will allow it to be used in applications like gas detection, military vehicle detection, industrial installation surveillance or agriculture. To do so, we have chosen Fourier transform imaging spectrometry using a birefringent lateral shearing interferometer. Thereafter, we have deeply studied wave propagation in such an interferometer to find out optimal geometries, and we have designed three prototypes: two in the mid-infrared, partially and entirely cooled, and the other in the far infrared spectral domain. The partially cooled prototype has been realized, characterized in the laboratory and tested on the field. This field campaign provided hyperspectral images on real operating conditions. Analysis of these images allowed us to estimate the performance of our system and to identify the points to be improved

Thesis (M.S.)--Indiana University, 2008.
Title from screen (viewed on June 3, 2009). Department of Earth Science, Indiana University-Purdue University Indianapolis (IUPUI). Advisor(s): Lin Li, Pierre Jacinthe, Gabriel M. Filippelli. Includes vita. Includes bibliographical references (leaves 78-81).

L’emballage joue un rôle important dans l’industrie alimentaire afin de maintenir la qualité des produits le plus longtemps possible. Les films de polymère sont largement utilisés dans l’emballage alimentaire et sont attrayants pour leurs propriétés exceptionnelles. Puisque les polymères à base de pétrole apportent des préoccupations environnementales, les polymères biodégradables tel que le PLA sont étudiés plus intensivement depuis quelques années considérant leurs propriétés écologiques. L’application de films renforcés permet, comparativement aux films simples, d’atteindre des fonctions spécifiques et d’améliorer leurs propriétés tel que l’étanchéité aux gaz. Toutefois, puisque la structure de ces films est plus complexe, le contrôle de qualité de ces derniers est plus difficile. Dans l’industrie, des méthodes hors-ligne sont très souvent utilisées pour effectuer le contrôle de qualité des films produits. Le contrôle est nécessaire puisque la variabilité de la matière première ainsi que le changement des conditions opératoires amènent des modifications qui changent considérablement les propriétés du film. Par conséquent, une inspection en temps réel ainsi qu’un contrôle des films de polymère est nécessaire sur la ligne de production afin d’obtenir un contrôle de qualité s’approchant de l’analyse en temps réel. Un système d’imagerie proche infrarouge (NIR) rapide et non-destructif est proposé pour caractériser les films biodégradables d’acide polylactique contenant du talc produits par extrusion-soufflage et utilisés pour l’emballage. Le but ultime est d’utiliser le système pour faire un contrôle de qualité sur la ligne d’extrusion ainsi qu’après le post-traitement termique, soit le recuit. Un ensemble d’échantillon de film de PLA contenant différentes concentrations en talc ont été fabriqués. Ces derniers ont ensuite été soumis à différentes conditions de recuit. Des images NIR ont été collectées avant la caractérisation des propriétés physiques et mécaniques ainsi que l’étanchéité aux gaz. Des techniques d’imagerie multivariées ont été appliquées aux images hyperspectrales. Celles-ci ont montré que la quantité de talc peut être déterminée et que l’information du spectre NIR permet de prédire les propriétés du film. Dans tous les cas, la méthode proposée permet de déterminer les variations dans les propriétés du film avec une bonne précision.
Food packaging plays a great role in the food industry to maintain food products quality as long as possible. Polymer films are widely used in food packaging and also attract attention because of their outstanding advantages. Since petroleum-based polymers are known to cause environmental concerns, biodegradable polymers like PLA were studied more intensively in recent years due to their environmentally friendly properties. The application of reinforced films exceeds simple ones in achieving specific functions and enhancing their properties such as barrier properties. Since the films structures are more complex, quality control is more challenging. In industry, off-line methods are vastly used for quality control of the produced films while variability in raw materials and processing conditions substantially change the film specifications. Consequently, real-time inspection and monitoring of polymer films is needed on the production line to achieve a real-time quality control of the films. A fast and non-invasive near-infrared (NIR) imaging system is proposed to characterize biodegradable polylactic acid (PLA) films containing talc, and produced by extrusion film-blowing for packaging applications. The ultimate goal is to use the system for quality control on the extrusion line, and after a post-processing via thermal treatment (annealing). A set of PLA-talc films with varying talc contents were produced and submitted to annealing under different conditions. NIR images of the films were collected after which the samples were characterized for their physical, mechanical, and gas barrier properties. Multivariate imaging techniques were then applied to the hyperspectral images. It is shown that various talc loadings can be distinguished, and the information contained in the NIR spectra allows predicting the film properties. In all cases, the proposed approach was able to track the variation in film properties with good accuracy

L’industrie et le domaine de la santé sont demandeurs de moyens rapides et peu couteux pour l’identification de microorganismes. Des avantages pratiques et un coût réduit font de la culture en boite de Petri un outil omniprésent en microbiologie, mais l’observation des colonies microbiennes n’offre pas de diagnostic fiable sans validation par une analyse secondaire. Ces analyses, qu’il s’agisse de réactions chimiques, d’une PCR ou de spectrométrie de masse, demandent une préparation d’échantillon spécifique impliquant des coûts et des délais supplémentaires. C’est pourquoi plusieurs systèmes d’imagerie de boite ont déjà été expérimentés pour automatiser l’observation des cultures et proposer une identification directement sur la boite de Petri. Toutefois, ceux-ci se cantonnent jusqu’à présent au domaine du visible et du proche infrarouge (400 – 1000 nm), ce qui n’apporte des informations que sur le morphotype des colonies de micro-organismes et limite la précision d’identification.Cette thèse est consacrée à l’exploration d’un système d’imagerie multispectrale dans l’infrarouge moyen. Cette gamme de longueurs d’onde apporte des informations à la fois sur le morphotype et sur la composition chimique des colonies observées. Cette imagerie non destructive et sans marquage pourrait fournir une identification à l’espèce des colonies cultivées sur agar, tout en ouvrant la voie à de nouvelles applications. Un système expérimental, combinant des lasers à cascade quantique comme source lumineuse et une matrice de microbolomètres comme imageur, a permis l’acquisition d’images de colonies à neuf longueurs d’ondes comprises entre 5 et 8 µm. 2253 colonies appartenant à huit espèces de microorganismes communs ont ainsi été imagées. Pour l’une des espèces, Staphylococcus epidermidis, trois souches différentes ont été analysées pour tester la capacité du système en matière de typage.Après acquisition, plusieurs méthodes de classification d’image ont été testées pour aboutir à un taux d’identification correct moyen de 94.4 %
Industry and health care are demanding rapid and inexpensive means for microbial identification. Thanks to its low cost and practical advantages, Petri dish culture is a ubiquitous tool in microbiology, but the sole observation of microbial colonies does not offer a reliable diagnosis. Identification in itself depends on secondary analysis, such as chemical reactions, PCR or mass spectrometry, which require specific sample preparation, which involves additional costs and delays. That is why several dish imaging systems have already been tested to automate the observation of cultures and to propose an identification directly on the Petri dish. However, these systems are generally limited to the visible and near infrared range (400 - 1000 nm), which only provides information on the morphotype of the microorganism colonies and therefore limits the identification accuracy.This thesis focuses on the development of a multispectral imaging system in the mid-infrared. In this wavelength range, images provide information on both the morphotype and the chemical composition of the observed colonies. This non-destructive and label-free imaging could provide species identification of colonies grown on agar, while opening the way to new applications. An experimental system, combining quantum cascade lasers as a light source and a microbolometers array as an imager, allowed the acquisition of images of colonies at nine wavelengths between 5 and 8 µm. 2253 colonies belonging to eight species of common microorganisms were imaged. For one of the species, Staphylococcus epidermidis, three different strains were analyzed to test the typing capabilities of the system.After acquisition, several image classification methods were tested to obtain an average correct identification rate of 94.4%

Hyper-Raman-Streuung folgt anderen Symmetrieauswahlregeln als Raman-Streuung und profitiert als nicht-linearer Zweiphotonenprozess noch mehr von verstärkten elektromagnetischen Feldern an der Oberfläche plasmonischer Nanostrukturen. Damit könnte die oberflächenverstärkte Hyper-Raman-Streuung (SEHRS) praktische Bedeutung in der Spektroskopie erlangen. Durch die Kombination von SEHRS und oberflächenverstärkter Raman-Streuung (SERS) können komplementäre Strukturinformationen erhalten werden. Diese eignen sich aufgrund der Lokalisierung der Verstärkung auf die unmittelbare Umgebung der Nanostrukturen besonders für die Charakterisierung der Wechselwirkung zwischen Molekülen und Metalloberflächen. Ziel dieser Arbeit war es, ein tieferes Verständnis des SEHRS-Effekts zu erlangen und dessen Anwendbarkeit für analytische Fragestellungen einzuschätzen. Dazu wurden SEHRS-Experimente mit Anregung bei 1064 nm und SERS-Experimente mit Anregung bei derselben Wellenlänge sowie mit Anregung bei 532 nm - für eine Detektion von SEHRS und SERS im gleichen Spektralbereich - durchgeführt. Als Beispiel für nicht-resonante Anregung wurden die vom pH-Wert abhängigen SEHRS- und SERS-Spektren von para-Mercaptobenzoesäure untersucht. Mit diesen Spektren wurde die Wechselwirkung verschiedener Silbernanostrukturen mit den Molekülen charakterisiert. Anhand von beta-Carotin wurden Einflüsse von Resonanzverstärkung im SEHRS-Experiment durch die gleichzeitige Anregung eines molekularen elektronischen Übergangs untersucht. Dabei wurde durch eine Thiolfunktionalisierung des Carotins eine intensivere Wechselwirkung mit der Silberoberfläche erzielt, sodass nicht nur resonante SEHRS- und SERS-Spektren, sondern auch nicht-resonante SERS-Spektren von Carotin erhalten werden konnten. Die Anwendbarkeit von SEHRS für hyperspektrale Kartierung in Verbindung mit Mikrospektroskopie wurde durch die Untersuchung von Verteilungen verschiedener Farbstoffe auf strukturierten plasmonischen Oberflächen demonstriert.
Hyper-Raman scattering follows different symmetry selection rules than Raman scattering and, as a non-linear two-photon process, profits even more than Raman scattering from enhanced electromagnetic fields at the surface of plasmonic nanostructures. Surface-enhanced hyper-Raman scattering (SEHRS) could thus gain practical importance for spectroscopy. The combination of SEHRS and surface-enhanced Raman scattering (SERS) offers complementary structural information. Specifically, due to the localization of the enhancement to the close proximity of the nanostructures, this information can be utilized for the characterization of the interaction between molecules and metal surfaces. The aim of this work was to increase the understanding of the SEHRS effect and to assess its applicability to answer analytical questions. For that purpose, SEHRS experiments with excitation at 1064 nm and SERS experiments with excitation at the same wavelength, as well as with excitation at 532 nm - to detect SEHRS and SERS in the same spectral region - were conducted. As an example for non-resonant excitation, pH-dependent SEHRS and SERS spectra of para-mercaptobenzoic acid were examined. Based on these spectra, the interaction of different silver nanostructures with the molecules was characterized. beta-Carotene was used to study the influence of resonance enhancement by the excitation of a molecular electronic transition during SEHRS experiments. By the thiol-functionalization of carotene, a more intense interaction with the silver surface was achieved, which enables to obtain not only resonant SEHRS and SERS but also non-resonant SERS spectra of carotene. Hyperspectral SEHRS imaging in combination with microspectroscopy was demonstrated by analyzing the distribution of different dyes on structured plasmonic surfaces.

Les propriétés optiques de nanotubes de carbone sont décrites idéalement parla physique d’un objet unidimensionnel, donnant lieu notamment à l’apparition des excitons pour décrire les transitions optiques de ces objets. Les expériences d’optique(émission, absorption) réalisées sur ces objets à température ambiante et sur des ensemble d’objets ont permis de confirmer les prédictions théoriques basées sur la physique des objets 1D. Mais à température cryogénique et à l’échelle de l’objet unique,les propriétés optiques observées expérimentalement sont systématiquement très éloignées de celles d’un objet 1D. On peut notamment citer l’apparition de propriétés comme l’émission de photons uniques, qui a largement contribué à l’intensification de la recherche sur ces objets pour des applications en photonique quantique. Ces propriétés sont attribuées à la localisation des excitons le long de l’axe des nanotubes dans des puits de potentiel créés aléatoirement par l’interaction des nanotubes avec leur environnement. Les propriétés optiques sont alors proches de celles des objets0D, et sont fortement modulées par l’environnement. Les mécanismes et l’origine de la localisation et la connaissance physique de ces puits sont encore très limités. Ce travail montre d’une part le développement d’une technique d’absorption sur objet individuel et la caractérisation de sa sensibilité, et d’autre part l’étude statistique de l’émission de nanotubes à température cryogénique. Les résultats obtenus par une technique de super-résolution couplée à une imagerie hyper-spectrale montrent les grandeurs caractéristiques des puits de potentiels au sein de nanotubes individuels.Un dispositif expérimental de photoluminescence résolue en excitation implémenté au cours de ce travail a également montré une modification de l’état excitonique fondamental par l’environnement, avec l’apparition d’une discrétisation spatiale et spectrale de l’état fondamental délocalisé en une multitude d’états localisés
The optical properties of carbon nanotubes are ideally described by the physicsof a one-dimensional object, giving rise in particular to the emergence of excitons todescribe the optical transitions of these objects. The optical experiments (emission,absorption) carried out on these objects at ambient temperature and on ensemblesconfirm the theoretical predictions based on the physics of 1D objects. But atcryogenic temperature and at the single emitter scale, the optical properties observedexperimentally are systematically different from those of a 1D object. One can citethe emergence of properties such as photon antibunching, which largely contributed tothe intensification of research on these objects for applications in quantum photonics.These properties are attributed to the localization of excitons along the nanotube axisin local potential wells (traps) created randomly by the interaction of nanotubes withtheir environment. The optical properties are then close to those of 0D objects, andare strongly modulated by the environment. The mechanisms and the origin of thelocalization and the physical knowledge of these traps are still very limited. This workshows on the one hand the development of an absorption setup on individual objectand the characterization of its sensitivity, and on the other hand the statistical studyof the emission of nanotubes at cryogenic temperature in a micro-photoluminescencesetup. The results obtained in the later setup by a super-resolution technique coupledwith hyper-spectral imaging show the characteristic quantities of potential wellswithin individual nanotubes. An experimental excitation-resolved photoluminescencesetup implemented during this work also showed a modification of the fundamentalexcitonic state by the environment, with the emergence of a spatial and spectraldiscretization of the delocalized ground state in a multitude of localized states

L'imagerie hyperspectrale consiste à acquérir une scène spatiale à plusieurs longueurs d'onde, de manière à reconstituer le spectre des pixels. Cette technique est utilisée en microscopie pour extraire des informations spectrales sur les spécimens observés. L'analyse de telles données est bien souvent difficile : lorsque l'image est observée à une résolution suffisamment fine, elle est dégradée par l'instrument (flou ou convolution) et une procédure de déconvolution doit être utilisée pour restaurer l'image originale. On parle ainsi de problème inverse, par opposition au problème direct consistant à modéliser la dégradation de l'image observée, étudié dans la première partie de la thèse. Un autre problème inverse important en imagerie consiste à extraire les signatures spectrales des composants purs de l'image ou sources et à estimer les contributions fractionnaires de chaque source à l'image. Cette procédure est qualifiée de séparation de sources, accomplie sous contrainte de positivité des sources et des mélanges. La deuxième partie propose des contributions algorithmiques en restauration d'images hyperspectrales. Le problème de déconvolution est formulé comme la minimisation d'un critère pénalisé et résolu à l'aide d'une structure de calcul rapide. Cette méthode générique est adaptée à la prise en compte de différents a priori sur la solution, tels que la positivité de l'image ou la préservation des contours. Les performances des techniques proposées sont évaluées sur des images de biocapteurs bactériens en microscopie confocale de fluorescence. La troisième partie de la thèse est axée sur la problématique de séparation de sources, abordé dans un cadre géométrique. Nous proposons une nouvelle condition suffisante d'identifiabilité des sources à partir des coefficients de mélange. Une étude innovante couplant le modèle d'observation instrumental avec le modèle de mélange de sources permet de montrer l'intérêt de la déconvolution comme étape préliminaire de la séparation. Ce couplage est validé sur des données acquises en microscopie confocale Raman.

Une nouvelle génération de spectromètres imageurs émerge dans le domaine de l'exploration spatiale par l'ajout d'une dimension supplémentaire de mesure, la dimension angulaire. L'imagerie spectroscopique multi-angulaire est conçue pour fournir une caractérisation plus précise des matériaux planétaires et permet une meilleure séparation des signaux provenant de l'atmosphère et la surface. Le capteur Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) à bord de la sonde Mars Reconnaissance Orbiter est une caméra hyperspectrale qui fonctionne systématiquement dans le mode multi-angulaire depuis l'orbite. Néanmoins, les images multi-angulaires hyperspectrales posent certains problèmes de manipulation, de visualisation et d'analyse en raison de leur taille et de leur complexité. Dans ce cadre, cette thèse propose des algorithmes statistiques et physiques pour analyser les images acquises par l'instrument CRISM de manière efficace et robuste. Premièrement, je propose une chaîne de post-traitement visant à améliorer la qualité radiométrique des données CRISM et à générer des produits améliorés, ces dernières données étant conçues pour permettre une analyse fine de la planète Mars. Deuxièmement, je m'intéresse à la correction atmosphérique des images CRISM en exploitant les capacités multi-angulaires de cet instrument. Un algorithme innovant, à base physique est mis en oeuvre pour compenser les effets atmosphériques afin d'estimer la reflectance de surface. Cette approche est particulièrement utilisée dans cette thèse pour déduire les propriétés photométriques des matériaux qui coexistent dans un site spécifique de Mars, le cratère de Gusev. Troisièmement, j'effectue une comparaison d'une sélection des meilleurs techniques existantes, visant à réaliser une déconvolution spectrale des données acquises par l'instrument CRISM. Ces techniques statistiques se sont avérées utiles lors de l'analyse d'images hyperspectrales de manière non supervisé, c'est a dire, sans aucun a priori sur la scène. Une stratégie originale est proposée pour discriminer les techniques les plus appropriées pour l'exploration de Mars, à partir de données indépendantes provenant d'autres capteurs d'imagerie haute résolution afin de construire une vérité de terrain
New generation of imaging spectrometers are emerging in the field of space exploration by adding an additional view of measurement, the angular dimension. Multi-angle imaging spectroscopy is conceived to provide a more accurate characterization of planetary materials and a higher success in separating the signals coming from the atmosphere and the surface. The Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) aboard the Mars Reconnaissance Orbiter is a hyperspectral camera that operates systematically in multi-angle mode from space. Nonetheless, multi-angle hyperspectral images are related to problems of manipulation, visualization and analysis because of their size and complexity. In this framework, this PhD thesis proposes robust statistical and physical algorithms to analyze images acquired by the CRISM instrument in an efficient manner. First, I propose a tailor-made data pipeline aimed at improving the radiometric quality of CRISM data and generating advanced products, the latter data being devised to perform fine analysis of the planet Mars. Second, I address the atmospheric correction of CRISM imagery by exploiting the multi-angle capabilities of this instrument. An innovative physically-based algorithm compensating for atmospheric effects is put forward in order to retrieve surface reflectance. This approach is particularly used in this thesis to infer the photometric properties of the materials coexisting in a specific site of Mars, the Gusev crater. Third, I perform an intercomparison of a selection of state-of-the-art techniques aimed at performing spectral unmixing of hyperspectral data acquired by the CRISM instrument. These statistical techniques are proved to be useful when analyzing hyperspectral images in an unsupervised manner, that is, without any a priori on the scene. An original strategy is proposed to discriminate the most suitable techniques for the exploration of Mars based on ground truth data built from independent high resolution imagery

博士
國立臺灣大學
生醫電子與資訊學研究所
99
This dissertation describes the construction of a hyperspectral imaging system (HSIS) based on Fourier transform spectroscopy (FTS) and the combinations of the HSIS with spectral analysis methods for biomedical applications. The FTS-based HSIS owns high-speed acquisition of hyperspectral imaging and simply optical design, which are critical features for biomedical applications. System performances and spectral calibration methods of the FTS-based HSIS were well tested. In the first biomedical application, we used the HSIS to measure scattering spectra from immobilized plasmonic nanoparticles. The current setup had acquisition time of 5 seconds and spectral resolution of 21.4 nm at 532.1 nm. We demonstrated the applicability of the HSIS in conjunction with spectral data analysis to quantify multiple types of plasmonic nanoparticles (PNPs) and detect small changes in localized surface plasmon resonance wavelengths of PNPs due to changes in the environmental refractive index. In the second application, we also applied hyperspectral imaging to measure spatially-resolved diffuse reflectance spectra (DRS) in the visible range and an iterative inversion method based on forward Monte Carlo (MC) modeling to quantify optical properties of two-layered tissue models. We validated the inversion method using spectra experimentally measured from liquid tissue mimicking phantoms with known optical properties. Results of fitting simulated data showed that simultaneously considering the spatial and spectral information in the inversion process improves the accuracies of estimating the optical properties and the top layer thickness in comparison to methods fitting reflectance spectra measured with a single source-detector separation or fitting spatially-resolved reflectance at a single wavelength. Further development of the method could improve noninvasive assessment of physiological status and pathological conditions of stratified squamous epithelium and superficial stroma.

Recent years have seen a push to provide a fast, sensitive, and quantitative diagnostic tool for biomedical applications. A search for new methods that can perform label-free and bond-specific determination of tissue and disease types with high spatial resolution is much desired. To address these needs, we have developed a mid-infrared photothermal system for sensitive and non-destructive characterization of samples. Our system utilizes a mid-infrared pump with a near-infrared probe for label-free spectroscopy and high spatial resolution imaging. In particular, this research focuses on optimization of the photothermal system, exploration of novel nonlinear photothermal phenomena, and development of a sub-diffraction limited mid-infrared imaging system. Photothermal spectroscopy is a pump-probe technique that utilizes a thermal lens effect in the sample for contrast. With the use of a high brightness mid-infrared pump laser, we extend photothermal spectroscopy into the mid-infrared regime for sensitive detection with high signal contrast. Targeting vibrational modes intrinsic to the sample allows for label-free characterization. Use of a fiber laser probe provides improved spatial resolution and takes advantage of the well-developed detector technology at near-infrared wavelengths. The research presented will be divided into three parts: optimization of the photothermal system, investigation of novel nonlinear photothermal phenomena, and photothermal spectroscopy and imaging for biomedical applications. Optimization of fiber laser design and experimental setup results in >100x increase in signal strength and over an order of magnitude improvement in signal contrast. With an optimized system, linear and nonlinear mid-infrared photothermal spectroscopy of a liquid crystal sample is demonstrated. For the first time, multiple bifurcations are reported in the nonlinear regime, shedding insight on the photothermal laser-matter interaction across phase transitions of a liquid crystal sample. Using a raster-scanning approach, sub-diffraction limited mid-infrared imaging is demonstrated. With this technique, various tissue types within the brain can be distinguished from one another, including differentiation between healthy and tumor tissue. Hyperspectral imaging of biological tissues demonstrates the potential of this technique to combine both spectral and spatial information for sample characterization. We present a photothermal system with the potential to meet the demands in drug and food safety, environmental monitoring, biomedicine, and security.
2018-11-02T00:00:00Z

This dissertation explores computational optical imaging methods to circumvent the physical limitations of classical sensing. An ideal imaging system would maximize resolution in time, spectral bandwidth, three-dimensional object space, and polarization. Practically, increasing any one parameter will correspondingly decrease the others.

Spectrometers strive to measure the power spectral density of the object scene. Traditional pushbroom spectral imagers acquire high resolution spectral and spatial resolution at the expense of acquisition time. Multiplexed spectral imagers acquire spectral and spatial information at each instant of time. Using a coded aperture and dispersive element, the coded aperture snapshot spectral imagers (CASSI) here described leverage correlations between voxels in the spatial-spectral data cube to compressively sample the power spectral density with minimal loss in spatial-spectral resolution while maintaining high temporal resolution.

Photography is limited by similar physical constraints. Low f/# systems are required for high spatial resolution to circumvent diffraction limits and allow for more photon transfer to the film plain, but require larger optical volumes and more optical elements. Wide field systems similarly suffer from increasing complexity and optical volume. Incorporating a multi-scale optical system, the f/#, resolving power, optical volume and wide field of view become much less coupled. This system uses a single objective lens that images onto a curved spherical focal plane which is relayed by small micro-optics to discrete focal planes. Using this design methodology allows for gigapixel designs at low f/# that are only a few pounds and smaller than a one-foot hemisphere.

Computational imaging systems add the necessary step of forward modeling and calibration. Since the mapping from object space to image space is no longer directly readable, post-processing is required to display the required data. The CASSI system uses an undersampled measurement matrix that requires inversion while the multi-scale camera requires image stitching and compositing methods for billions of pixels in the image. Calibration methods and a testbed are demonstrated that were developed specifically for these computational imaging systems.

Dissertation

The agriculture industry experiences severe economic losses each year when wheat crops become infected with Fusarium and the mycotoxin Deoxynivalenol (DON). This research investigated the feasibility of using near infrared hyperspectral imaging to detect Fusarium damage and DON in Canadian Western Red Spring wheat. Four samples were selected from each grain grade resulting in 16 samples and 240 hyperspectral data cubes. The data cubes were calibrated to the system, the consistent spectra was found and then a 1- nearest neighbour classifier was generated. Grade percentages were computed and used to generate two 3- nearest neighbour classifiers, one for identifying Fusarium damage and the other for identifying DON content. The Fusarium damage classifier had an accuracy of 85% and the DON content classifier had an accuracy of 80%. While a single sample image classification will not replace manual testing, the use of multiple samples from one harvest could reduce manual inspections.

Les nanomatériaux sont une classe de contaminants qui est de plus en plus présent dans l’environnement. Leur impact sur l’environnement dépendra de leur persistance, mobilité, toxicité et bioaccumulation. Chacun de ces paramètres dépendra de leur comportement physicochimique dans les eaux naturelles (i.e. dissolution et agglomération). L’objectif de cette étude est de comprendre l’agglomération et l’hétéroagglomération des nanoparticules d’argent dans l’environnement. Deux différentes sortes de nanoparticules d’argent (nAg; avec enrobage de citrate et avec enrobage d’acide polyacrylique) de 5 nm de diamètre ont été marquées de manière covalente à l’aide d’un marqueur fluorescent et ont été mélangées avec des colloïdes d’oxyde de silice (SiO2) ou d’argile (montmorillonite). L’homo- et hétéroagglomération des nAg ont été étudiés dans des conditions représentatives d’eaux douces naturelles (pH 7,0; force ionique 10 7 à 10-1 M de Ca2+). Les tailles ont été mesurées par spectroscopie de corrélation par fluorescence (FCS) et les résultats ont été confirmés à l’aide de la microscopie en champ sombre avec imagerie hyperspectrale (HSI). Les résultats ont démontrés que les nanoparticules d’argent à enrobage d’acide polyacrylique sont extrêmement stables sous toutes les conditions imposées, incluant la présence d’autres colloïdes et à des forces ioniques très élevées tandis que les nanoparticules d’argent avec enrobage de citrate ont formées des hétéroagrégats en présence des deux particules colloïdales.
Nanomaterials are a class of contaminants that are increasingly found in the natural environment. Their environmental risk will depend on their persistence, mobility, toxicity and bioaccumulation. Each of these parameters will depend strongly upon their physicochemical fate (dissolution, agglomeration) in natural waters. The goal of this paper is to understand the agglomeration and heteroagglomeration of silver nanoparticles in the environment. Two different silver nanoparticles (nAg; citrate coated and polyacrylic acid coated) with a diameter of 5 nm were covalently labelled with a fluorescent dye and then mixed with colloidal silicon oxides (SiO2) and clays (montmorillonite). The homo- and heteroagglomeration of the silver nanoparticles were then studied in waters that were representative of natural freshwaters (pH 7.0; ionic strength 10-7 to 10-1 M of Ca2+). Sizes were followed by fluorescence correlation spectroscopy (FCS) and results were validated using enhanced darkfield microscopy with hyperspectral imaging (HSI). Results have demonstrated that the polyacrylic acid coated nAg was extremely stable under all conditions, including in the presence of other colloids and at high ionic strength, whereas the citrate coated nAg formed heteroagregates in the presence of both natural colloidal particles.

Measurement science has seen fast growth of data in both volume and complexity in recent years, new algorithms and methodologies have been developed to aid the decision
making in measurement sciences, and this process is automated for the liberation of labor. In light of the adversarial approaches shown in digital image processing, Chapter 2 demonstrate how the same attack is possible with spectroscopic data. Chapter 3 takes the question presented in Chapter 2 and optimized the classifier through an iterative approach. The optimized LDA was cross-validated and compared with other standard chemometrics methods, the application was extended to bi-distribution mineral Raman data. Chapter 4 focused on a novel Artificial Neural Network structure design with diffusion measurements; the architecture was tested both with simulated dataset and experimental dataset. Chapter 5 presents the construction of a novel infrared hyperspectral microscope for complex chemical compound classification, with detailed discussion in the segmentation of the images and choice of a classifier to choose.

Forests can be considered as one of the most important Earth's ecosystems not only because of oxygen production and carbon sequestration via photosynthesis, but also as a source of many natural resources (such as wood) and as a habitat of many specific plants and animals. Monitoring of forest health status is thus crucial activity for keeping all production and ecosystem functions of forests. The main aim of the thesis is development of an alternative approach for forest health status based on airborne hyperspectral data (HyMap) analysis supported by field sampling. The proposed approach tries to use similar vegetation parameters which are used in case of the current methods of forest health status assessment based on field inspections. It is believed that importance of such new methods will significantly increase in the time when the planned satellite hyperspectral missions (e.g. EnMap) will move into operational phase. The developed forest health monitoring approach is practically demonstrated on mature Norway spruce (Picea abies L. Karst) forests of the Sokolov lignite basin which were affected by long-term coal mining and heavy industry and therefore high variability of forest health status was assumed in this case. Two leaf level radiative transfer models were used for simulating spectral...