Dissertations / Theses on the topic 'Inverse imaging'
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Lecharlier, Loïc. "Blind inverse imaging with positivity constraints." Doctoral thesis, Universite Libre de Bruxelles, 2014. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209240.
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Dans les problèmes inverses en imagerie, on suppose généralement connu l’opérateur ou matrice décrivant le système de formation de l’image. De façon équivalente pour un système linéaire, on suppose connue sa réponse impulsionnelle. Toutefois, ceci n’est pas une hypothèse réaliste pour de nombreuses applications pratiques pour lesquelles cet opérateur n’est en fait pas connu (ou n’est connu qu’approximativement). On a alors affaire à un problème d’inversion dite “aveugle”. Dans le cas de systèmes invariants par translation, on parle de “déconvolution aveugle” car à la fois l’image ou objet de départ et la réponse impulsionnelle doivent être estimées à partir de la seule image observée qui résulte d’une convolution et est affectée d’erreurs de mesure. Ce problème est notoirement difficile et pour pallier les ambiguïtés et les instabilités numériques inhérentes à ce type d’inversions, il faut recourir à des informations ou contraintes supplémentaires, telles que la positivité qui s’est avérée un levier de stabilisation puissant dans les problèmes d’imagerie non aveugle. La thèse propose de nouveaux algorithmes d’inversion aveugle dans un cadre discret ou discrétisé, en supposant que l’image inconnue, la matrice à inverser et les données sont positives. Le problème est formulé comme un problème d’optimisation (non convexe) où le terme d’attache aux données à minimiser, modélisant soit le cas de données de type Poisson (divergence de Kullback-Leibler) ou affectées de bruit gaussien (moindres carrés), est augmenté par des termes de pénalité sur les inconnues du problème. La stratégie d’optimisation consiste en des ajustements alternés de l’image à reconstruire et de la matrice à inverser qui sont de type multiplicatif et résultent de la minimisation de fonctions coût “surrogées” valables dans le cas positif. Le cadre assez général permet d’utiliser plusieurs types de pénalités, y compris sur la variation totale (lissée) de l’image. Une normalisation éventuelle de la réponse impulsionnelle ou de la matrice est également prévue à chaque itération. Des résultats de convergence pour ces algorithmes sont établis dans la thèse, tant en ce qui concerne la décroissance des fonctions coût que la convergence de la suite des itérés vers un point stationnaire. La méthodologie proposée est validée avec succès par des simulations numériques relatives à différentes applications telle que la déconvolution aveugle d'images en astronomie, la factorisation en matrices positives pour l’imagerie hyperspectrale et la déconvolution de densités en statistique.Doctorat en Sciences
info:eu-repo/semantics/nonPublished
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Javanmard, Mehdi. "Inverse problem approach to ultrasound medical imaging." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape17/PQDD_0001/NQ31933.pdf.
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Leung, Wun Ying Valerie. "Inverse problems in astronomical and general imaging." Thesis, University of Canterbury. Electrical and Computer Engineering, 2002. http://hdl.handle.net/10092/7513.
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The resolution and the quality of an imaged object are limited by four contributing factors. Firstly, the primary resolution limit of a system is imposed by the aperture of an instrument due to the effects of diffraction. Secondly, the finite sampling frequency, the finite measurement time and the mechanical limitations of the equipment also affect the resolution of the images captured. Thirdly, the images are corrupted by noise, a process inherent to all imaging systems. Finally, a turbulent imaging medium introduces random degradations to the signals before they are measured. In astronomical imaging, it is the atmosphere which distorts the wavefronts of the objects, severely limiting the resolution of the images captured by ground-based telescopes. These four factors affect all real imaging systems to varying degrees.
All the limitations imposed on an imaging system result in the need to deduce or reconstruct the underlying object distribution from the distorted measured data. This class of problems is called inverse problems. The key to the success of solving an inverse problem is the correct modelling of the physical processes which give rise to the corresponding forward problem. However, the physical processes have an infinite amount of information, but only a finite number of parameters can be used in the model. Information loss is therefore inevitable. As a result, the solution to many inverse problems requires additional information or prior knowledge. The application of prior information to inverse problems is a recurrent theme throughout this thesis.
An inverse problem that has been an active research area for many years is interpolation, and there exist numerous techniques for solving this problem. However, many of these techniques neither account for the sampling process of the instrument nor include prior information in the reconstruction. These factors are taken into account in the proposed optimal Bayesian interpolator. The process of interpolation is also examined from the point of view of superresolution, as these processes can be viewed as being complementary.
Since the principal effect of atmospheric turbulence on an incoming wavefront is a phase distortion, most of the inverse problem techniques devised for this seek to either estimate or compensate for this phase component. These techniques are classified into computer post-processing methods, adaptive optics (AO) and hybrid techniques.
Blind deconvolution is a post-processing technique which uses the speckle images to estimate both the object distribution and the point spread function (PSF), the latter of which is directly related to the phase. The most successful approaches are based on characterising the PSF as the aberrations over the aperture. Since the PSF is also dependent on the atmosphere, it is possible to constrain the solution using the statistics of the atmosphere. An investigation shows the feasibility of this approach. Bispectrum is also a post-processing method which reconstructs the spectrum of the object. The key component for phase preservation is the property of phase closure, and its application as prior information for blind deconvolution is examined.
Blind deconvolution techniques utilise only information in the image channel to estimate the phase which is difficult. An alternative method for phase estimation is from a Shack-Hartmann (SH) wavefront sensing channel. However, since phase information is present in both the wavefront sensing and the image channels simultaneously, both of these approaches suffer from the problem that phase information from only one channel is used. An improved estimate of the phase is achieved by a combination of these methods, ensuring that the phase estimation is made jointly from the data in both the image and the wavefront sensing measurements. This formulation, posed as a blind deconvolution framework, is investigated in this thesis. An additional advantage of this approach is that since speckle images are imaged in a narrowband, while wavefront sensing images are captured by a charge-coupled device (CCD) camera at all wavelengths, the splitting of the light does not compromise the light level for either channel. This provides a further incentive for using simultaneous data sets.
The effectiveness of using Shack-Hartmann wavefront sensing data for phase estimation relies on the accuracy of locating the data spots. The commonly used method which calculates the centre of gravity of the image is in fact prone to noise and is suboptimal. An improved method for spot location based on blind deconvolution is demonstrated.
Ground-based adaptive optics (AO) technologies aim to correct for atmospheric turbulence in real time. Although much success has been achieved, the space- and time-varying nature of the atmosphere renders the accurate measurement of atmospheric properties difficult. It is therefore usual to perform additional post-processing on the AO data. As a result, some of the techniques developed in this thesis are applicable to adaptive optics.
One of the methods which utilise elements of both adaptive optics and post-processing is the hybrid technique of deconvolution from wavefront sensing (DWFS). Here, both the speckle images and the SH wavefront sensing data are used. The original proposal of DWFS is simple to implement but suffers from the problem where the magnitude of the object spectrum cannot be reconstructed accurately. The solution proposed for overcoming this is to use an additional set of reference star measurements. This however does not completely remove the original problem; in addition it introduces other difficulties associated with reference star measurements such as anisoplanatism and reduction of valuable observing time. In this thesis a parameterised solution is examined which removes the need for a reference star, as well as offering a potential to overcome the problem of estimating the magnitude of the object.
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Papadopoulos, Timoleon. "Inverse filtering for virtual acoustic imaging systems." Thesis, University of Southampton, 2006. https://eprints.soton.ac.uk/157421/.
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The research topic of this thesis is the use of inverse filtering for the design and implementation of two-channel virtual acoustic imaging systems that utilise loudspeakers. The basic objective of such systems is to invert the electroacoustic plant between the input to the loudspeakers and the output at the listener’s ears and hence make it possible for a pair of binaural signals to be locally reproduced at the position of the listener’s ears. As a starting point for the research presented, a previously introduced type of inverse filtering design is considered in which the inverse is implemented with FIR filters. The basic formulation of this design is described and a number of innovative points regarding its implementation are made. An experimental procedure is then formulated for the evaluation of the effectiveness of this inverse filtering design that is based on objective measurements of the inversion process. Unlike previously employed methods that are based on computer simulations or subjective experiments, the introduced experimental procedure is shown to be very efficient in isolating and exactly quantifying the effect on the accuracy of the inversion of a number of errors and approximations typically present in the implementation. A detailed evaluation is thus presented of the inverse filtering design at hand in realistic conditions of implementation. Subsequently, a novel method for the off-line implementation of the inverse filtering is presented that utilises recursive filters of lower order. In this method, the responses of the inverse filters are decomposed into two parts, one realisable in forward time and one in backward time. The effectiveness of this new method for the implementation of the inverse is tested and compared with a small selection of the objective evaluation results described above. Finally, an algorithm for the on-line implementation of the forward-backward inverse filtering is proposed and its computational cost is compared with the currently available frequency-domain block-processing filtering algorithms.
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Gregson, James. "Applications of inverse problems in fluids and imaging." Thesis, University of British Columbia, 2015. http://hdl.handle.net/2429/54081.
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Three applications of inverse problems relating to fluid imaging and image deblurring are presented. The first two, tomographic reconstruction of dye concentration fields from multi-view video and deblurring of photographs, are addressed by a stochastic optimization scheme that allows a wide variety of priors to be incorporated into the reconstruction process within a straightforward framework. The third, estimation of fluid velocities from volumetric dye concentration fields, highlights a previously unexplored connection between fluid simulation and proximal algorithms from convex optimization. This connection allows several classical imaging inverse problems to be investigated in the context of fluids, including optical flow, denoising and deconvolution. The connection also allows inverse problems to be incorporated into fluid simulation for the purposes of physically-based regularization of optical flow and for stylistic modifications of fluid captures. Through both methods and all three applications the importance of incorporating domain-specific priors into inverse problems for fluids and imaging is highlighted.Science, Faculty of
Computer Science, Department of
Graduate
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Li, Xiaobei. "Instrumentation and inverse problem solving for impedance imaging /." Thesis, Connect to this title online; UW restricted, 2006. http://hdl.handle.net/1773/5973.
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Oster, Howard Steven. "Electrocardiographic imaging: New applications and new inverse methodology." Case Western Reserve University School of Graduate Studies / OhioLINK, 1995. http://rave.ohiolink.edu/etdc/view?acc_num=case1058380620.
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Szasz, Teodora. "Advanced beamforming techniques in ultrasound imaging and the associated inverse problems." Thesis, Toulouse 3, 2016. http://www.theses.fr/2016TOU30221/document.
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L'imagerie ultrasonore (US) permet de réaliser des examens médicaux non invasifs avec des méthodes d'acquisition rapides à des coûts modérés. L'imagerie cardiaque, abdominale, fœtale, ou mammaire sont quelques-unes des applications où elle est largement utilisée comme outil de diagnostic. En imagerie US classique, des ondes acoustiques sont transmises à une région d'intérêt du corps humain. Les signaux d'écho rétrodiffusés, sont ensuite formés pour créer des lignes radiofréquences. La formation de voies (FV) joue un rôle clé dans l'obtention des images US, car elle influence la résolution et le contraste de l'image finale. L'objectif de ce travail est de modéliser la formation de voies comme un problème inverse liant les données brutes aux signaux RF. Le modèle de formation de voies proposé ici améliore le contraste et la résolution spatiale des images échographiques par rapport aux techniques de FV existants. Dans un premier temps, nous nous sommes concentrés sur des méthodes de FV en imagerie US. Nous avons brièvement passé en revue les techniques de formation de voies les plus courantes, en commencent par la méthode par retard et somme standard puis en utilisant les techniques de formation de voies adaptatives. Ensuite, nous avons étudié l'utilisation de signaux qui exploitent une représentation parcimonieuse de l'image US dans le cadre de la formation de voies. Les approches proposées détectent les réflecteurs forts du milieu sur la base de critères bayésiens. Nous avons finalement développé une nouvelle façon d'aborder la formation de voies en imagerie US, en la formulant comme un problème inverse linéaire liant les échos réfléchis au signal final. L'intérêt majeur de notre approche est la flexibilité dans le choix des hypothèses statistiques sur le signal avant la formation de voies et sa robustesse dans à un nombre réduit d'émissions. Finalement, nous présentons une nouvelle méthode de formation de voies pour l'imagerie US basée sur l'utilisation de caractéristique statistique des signaux supposée alpha-stableUltrasound (US) allows non-invasive and ultra-high frame rate imaging procedures at reduced costs. Cardiac, abdominal, fetal, and breast imaging are some of the applications where it is extensively used as diagnostic tool. In a classical US scanning process, short acoustic pulses are transmitted through the region-of-interest of the human body. The backscattered echo signals are then beamformed for creating radiofrequency(RF) lines. Beamforming (BF) plays a key role in US image formation, influencing the resolution and the contrast of final image. The objective of this thesis is to model BF as an inverse problem, relating the raw channel data to the signals to be recovered. The proposed BF framework improves the contrast and the spatial resolution of the US images, compared with the existing BF methods. To begin with, we investigated the existing BF methods in medical US imaging. We briefly review the most common BF techniques, starting with the standard delay-and-sum BF method and emerging to the most known adaptive BF techniques, such as minimum variance BF. Afterwards, we investigated the use of sparse priors in creating original two-dimensional beamforming methods for ultrasound imaging. The proposed approaches detect the strong reflectors from the scanned medium based on the well-known Bayesian Information Criteria used in statistical modeling. Furthermore, we propose a new way of addressing the BF in US imaging, by formulating it as a linear inverse problem relating the reflected echoes to the signal to be recovered. Our approach offers flexibility in the choice of statistical assumptions on the signal to be beamformed and it is robust to a reduced number of pulse emissions. At the end of this research, we investigated the use of the non-Gaussianity properties of the RF signals in the BF process, by assuming alpha-stable statistics of US images
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Zhu, Sha. "A Bayesian Approach for Inverse Problems in Synthetic Aperture Radar Imaging." Phd thesis, Université Paris Sud - Paris XI, 2012. http://tel.archives-ouvertes.fr/tel-00844748.
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Synthetic Aperture Radar (SAR) imaging is a well-known technique in the domain of remote sensing, aerospace surveillance, geography and mapping. To obtain images of high resolution under noise, taking into account of the characteristics of targets in the observed scene, the different uncertainties of measure and the modeling errors becomes very important.Conventional imaging methods are based on i) over-simplified scene models, ii) a simplified linear forward modeling (mathematical relations between the transmitted signals, the received signals and the targets) and iii) using a very simplified Inverse Fast Fourier Transform (IFFT) to do the inversion, resulting in low resolution and noisy images with unsuppressed speckles and high side lobe artifacts.In this thesis, we propose to use a Bayesian approach to SAR imaging, which overcomes many drawbacks of classical methods and brings high resolution, more stable images and more accurate parameter estimation for target recognition.The proposed unifying approach is used for inverse problems in Mono-, Bi- and Multi-static SAR imaging, as well as for micromotion target imaging. Appropriate priors for modeling different target scenes in terms of target features enhancement during imaging are proposed. Fast and effective estimation methods with simple and hierarchical priors are developed. The problem of hyperparameter estimation is also handled in this Bayesian approach framework. Results on synthetic, experimental and real data demonstrate the effectiveness of the proposed approach.
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Rückert, Nadja. "Studies on two specific inverse problems from imaging and finance." Doctoral thesis, Universitätsbibliothek Chemnitz, 2012. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-91587.
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This thesis deals with regularization parameter selection methods in the context of Tikhonov-type regularization with Poisson distributed data, in particular the reconstruction of images, as well as with the identification of the volatility surface from observed option prices.
In Part I we examine the choice of the regularization parameter when reconstructing an image, which is disturbed by Poisson noise, with Tikhonov-type regularization. This type of regularization is a generalization of the classical Tikhonov regularization in the Banach space setting and often called variational regularization. After a general consideration of Tikhonov-type regularization for data corrupted by Poisson noise, we examine the methods for choosing the regularization parameter numerically on the basis of two test images and real PET data.
In Part II we consider the estimation of the volatility function from observed call option prices with the explicit formula which has been derived by Dupire using the Black-Scholes partial differential equation. The option prices are only available as discrete noisy observations so that the main difficulty is the ill-posedness of the numerical differentiation. Finite difference schemes, as regularization by discretization of the inverse and ill-posed problem, do not overcome these difficulties when they are used to evaluate the partial derivatives. Therefore we construct an alternative algorithm based on the weak formulation of the dual Black-Scholes partial differential equation and evaluate the performance of the finite difference schemes and the new algorithm for synthetic and real option prices.
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Ram, Sundaresh, and Sundaresh Ram. "Sparse Representations and Nonlinear Image Processing for Inverse Imaging Solutions." Diss., The University of Arizona, 2017. http://hdl.handle.net/10150/626164.
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This work applies sparse representations and nonlinear image processing to two inverse imaging problems. The first problem involves image restoration, where the aim is to reconstruct an unknown high-quality image from a low-quality observed image. Sparse representations of images have drawn a considerable amount of interest in recent years. The assumption that natural signals, such as images, admit a sparse decomposition over a redundant dictionary leads to efficient algorithms for handling such sources of data. The standard sparse representation, however, does not consider the intrinsic geometric structure present in the data, thereby leading to sub-optimal results. Using the concept that a signal is block sparse in a given basis —i.e., the non-zero elements occur in clusters of varying sizes — we present a novel and efficient algorithm for learning a sparse representation of natural images, called graph regularized block sparse dictionary (GRBSD) learning. We apply the proposed method towards two image restoration applications: 1) single-Image super-resolution, where we propose a local regression model that uses learned dictionaries from the GRBSD algorithm for super-resolving a low-resolution image without any external training images, and 2) image inpainting, where we use GRBSD algorithm to learn a multiscale dictionary to generate visually plausible pixels to fill missing regions in an image. Experimental results validate the performance of the GRBSD learning algorithm for single-image super-resolution and image inpainting applications. The second problem addressed in this work involves image enhancement for detection and segmentation of objects in images. We exploit the concept that even though data from various imaging modalities have high dimensionality, the data is sufficiently well described using low-dimensional geometrical structures. To facilitate the extraction of objects having such structure, we have developed general structure enhancement methods that can be used to detect and segment various curvilinear structures in images across different applications. We use the proposed method to detect and segment objects of different size and shape in three applications: 1) segmentation of lamina cribrosa microstructure in the eye from second-harmonic generation microscopy images, 2) detection and segmentation of primary cilia in confocal microscopy images, and 3) detection and segmentation of vehicles in wide-area aerial imagery. Quantitative and qualitative results show that the proposed methods provide improved detection and segmentation accuracy and computational efficiency compared to other recent algorithms.
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Som, Subhojit. "Topics in Sparse Inverse Problems and Electron Paramagnetic Resonance Imaging." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1282135281.
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Zhang, Wenlong. "Forward and Inverse Problems Under Uncertainty." Thesis, Paris Sciences et Lettres (ComUE), 2017. http://www.theses.fr/2017PSLEE024/document.
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Cette thèse contient deux matières différentes. Dans la première partie, deux cas sont considérés. L'un est le modèle plus lisse de la plaque mince et l'autre est les équations des limites elliptiques avec des données limites incertaines. Dans cette partie, les convergences stochastiques des méthodes des éléments finis sont prouvées pour chaque problème.Dans la deuxième partie, nous fournissons une analyse mathématique du problème inverse linéarisé dans la tomographie d'impédance électrique multifréquence. Nous présentons un cadre mathématique et numérique pour une procédure d'imagerie du tenseur de conductivité électrique anisotrope en utilisant une nouvelle technique appelée Tentomètre de diffusion Magnéto-acoustographie et proposons une approche de contrôle optimale pour reconstruire le facteur de propriété intrinsèque reliant le tenseur de diffusion au tenseur de conductivité électrique anisotrope. Nous démontrons la convergence et la stabilité du type Lipschitz de l'algorithme et présente des exemples numériques pour illustrer sa précision. Le modèle cellulaire pour Electropermécanisme est démontré. Nous étudions les paramètres efficaces dans un modèle d'homogénéisation. Nous démontrons numériquement la sensibilité de ces paramètres efficaces aux paramètres microscopiques critiques régissant l'électropermécanismeThis thesis contains two different subjects. In first part, two cases are considered. One is the thin plate spline smoother model and the other one is the elliptic boundary equations with uncertain boundary data. In this part, stochastic convergences of the finite element methods are proved for each problem.In second part, we provide a mathematical analysis of the linearized inverse problem in multifrequency electrical impedance tomography. We present a mathematical and numerical framework for a procedure of imaging anisotropic electrical conductivity tensor using a novel technique called Diffusion Tensor Magneto-acoustography and propose an optimal control approach for reconstructing the cross-property factor relating the diffusion tensor to the anisotropic electrical conductivity tensor. We prove convergence and Lipschitz type stability of the algorithm and present numerical examples to illustrate its accuracy. The cell model for Electropermeabilization is demonstrated. We study effective parameters in a homogenization model. We demonstrate numerically the sensitivity of these effective parameters to critical microscopic parameters governing electropermeabilization
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Guan, Lim Kian. "Battle damage assessment using Inverse Synthetic Aperture Radar (ISAR) /." Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2004. http://library.nps.navy.mil/uhtbin/hyperion/04Dec%5FGuan.pdf.
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Thesis (M.S. in Combat Systems Technology)--Naval Postgraduate School, Dec. 2004.Thesis Advisor(s): Brett H. Borden, Donald L. Walters. Includes bibliographical references (p. 97-98). Also available online.
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Travis, Clive Hathaway. "The inverse problem and applications to optical and eddy current imaging." Thesis, University of Surrey, 1989. http://epubs.surrey.ac.uk/804869/.
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Zamanian, Sam Ahmad. "Hierarchical Bayesian approaches to seismic imaging and other geophysical inverse problems." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/92970.
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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 189-196).
In many geophysical inverse problems, smoothness assumptions on the underlying geologic model are utilized to mitigate the effects of poor data coverage and observational noise and to improve the quality of the inferred model parameters. In the context of Bayesian inference, these smoothness assumptions take the form of a prior distribution on the model parameters. Conventionally, the regularization parameters defining these assumptions are fixed independently from the data or tuned in an ad hoc manner. However, it is often the case that the smoothness properties of the true earth model are not known a priori, and furthermore, these properties may vary spatially. In the seismic imaging problem, for example, where the objective is to estimate the earth's reflectivity, the reflectivity model is smooth along a particular reflector but exhibits a sharp contrast in the direction orthogonal to the reflector. In such cases, defining a prior using predefined smoothness assumptions may result in posterior estimates of the model that incorrectly smooth out these sharp contrasts. In this thesis, we explore the application of Bayesian inference to different geophysical inverse problems and seek to address issues related to smoothing by appealing to the hierarchical Bayesian framework. We capture the smoothness properties of the prior distribution on the model by defining a Markov random field (MRF) on the set of model parameters and assigning weights to the edges of the underlying graph; we refer to these parameters as the edge strengths of the MRF. We investigate two cases where the smoothing is specified a priori and introduce a method for estimating the edge strengths of the MRF. In the first part of this thesis, we apply a Bayesian inference framework (where the edge strengths of the MRF are predetermined) to the problem of characterizing the fractured nature of a reservoir from seismic data. Our methodology combines different features of the seismic data, particularly P-wave reflection amplitudes and scattering attributes, to allow for estimation of fracture properties under a larger physical regime than would be attainable using only one of these data types. Through this application, we demonstrate the capability of our parameterization of the prior distribution with edge strengths to both enforce smoothness in the estimates of the fracture properties and capture a priori information about geological features in the model (such as a discontinuity that may arise in the presence of a fault). We solve the inference problem via loopy belief propagation to approximate the posterior marginal distributions of the fracture properties, as well as their maximum a posteriori (MAP) and Bayes least squares estimates. In the second part of the thesis, we investigate how the parameters defining the prior distribution are connected to the model covariance and address the question of how to optimize these parameters in the context of the seismic imaging problem. We formulate the seismic imaging problem within the hierarchical Bayesian setting, where the edge strengths are treated as random variables to be inferred from the data, and provide a framework for computing the marginal MAP estimate of the edge strengths by application of the expectation-maximization (E-M) algorithm. We validate our methodology on synthetic datasets arising from 2-D models. The images we obtain after inferring the edge strengths exhibit the desired spatially-varying smoothness properties and yield sharper, more coherent reflectors. In the final part of the thesis, we shift our focus and consider the problem of timelapse seismic processing, where the objective is to detect changes in the subsurface over a period of time using repeated seismic surveys. We focus on the realistic case where the surveys are taken with differing acquisition geometries. In such situations, conventional methods for processing time-lapse data involve inverting surveys separately and subtracting the inversion models to estimate the change in model parameters; however, such methods often perform poorly as they do not correctly account for differing model uncertainty between surveys due to differences in illumination and observational noise. Applying the machinery explored in the previous chapters, we formulate the time-lapse processing problem within the hierarchical Bayesian setting and present a framework for computing the marginal MAP estimate of the time-lapse change model using the E-M algorithm. The results of our inference framework are validated on synthetic data from a 2-D time-lapse seismic imaging example, where the hierarchical Bayesian estimates significantly outperform conventional time-lapse inversion results.
by Sam Ahmad Zamanian.
Ph. D.
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Bhandari, Ayush. "Inverse problems in time-of-flight imaging : theory, algorithms and applications." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/95867.
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Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2014.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 100-108).
Time-of-Fight (ToF) cameras utilize a combination of phase and amplitude information to return real-time, three dimensional information of a scene in form of depth images. Such cameras have a number of scientific and consumer oriented applications. In this work, we formalize a mathematical framework that leads to unifying perspective on tackling inverse problems that arise in the ToF imaging context. Starting from first principles, we discuss the implications of time and frequency domain sensing of a scene. From a linear systems perspective, this amounts to an operator sampling problem where the operator depends on the physical parameters of a scene or the bio-sample being investigated. Having presented some examples of inverse problems, we discuss detailed solutions that benefit from scene based priors such sparsity and rank constraints. Our theory is corroborated by experiments performed using ToF/Kinect cameras. Applications of this work include multi-bounce light decomposition, ultrafast imaging and fluorophore lifetime estimation.
by Ayush Bhandari.
S.M.
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Rangarajan, Ranjani. "Inverse Synthetic Aperture Radar Imaging for Multiple Targets Using Compressed Sensing." University of Cincinnati / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1416233543.
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DACHENA, CHIARA. "Microwave Imaging of The Neck by Means of Inverse-Scattering Techniques." Doctoral thesis, Università degli studi di Genova, 2023. https://hdl.handle.net/11567/1108293.
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In recent decades, in the field of applied electromagnetism, there has been a significant interest in the development of non-invasive diagnostic methods through the use of electromagnetic waves, especially at microwave frequencies [1]. Microwave imaging (MWI) - considered for a long period an emerging technique - has potential- ities in numerous, and constantly increasing, applications in different areas, ranging from civil and industrial engineering, with non-destructive testing and evaluations
(example e.g., monitoring contamination in food, sub-surface imaging based on both terrestrial and space platforms; detection of cracks and defects in structures and equipments of various kinds; antennas diagnostics, etc. ), up to the biomedical field [2], [3], [4], [5], [6], [7]. One of the first applications of microwave imaging (MWI) in the medical field was the detection of breast tumors [8], [9], [10], [11], [12], [13], [14], [15], [16], [17]. Subsequently, brain stroke detection has received great attention [18],[19], [20], too. Other possible clinical applications include imaging of torso, arms, and other body parts [21], [22], [23], [24]. The standard diagnostic method are computerized tomography (CT), nuclear magnetic resonance (NMR) and X-rays. Although these consolidated techniques are able to provide extraordinary diagnostic results, some limitations still exist that stimulate the continuous research of new imaging solutions. In this context, MWI can be overcome some limitations of these techniques, such as the ionizing radiations in the CT and X-rays or the disadvantages of being expensive, in the NMR case. This motivates the study of MWI methods and systems, at least as a complementary diagnostic tools.
The aim of electromagnetic diagnostic techniques is to determine physical param- eters (such as the electrical conductivity and the dielectric permittivity of materials) and/or geometrics of the objects under test, which are suppose contained within a certain space region, sometimes denoted as "investigation domain". In particular, by means of a properly designed transmitting antenna, the object under test is
illuminated by an electromagnetic radiation. The interaction between the incident radiation and the target causes the so-called electromagnetic scattering phenomena. The field generated by this interaction can be measured around the object by means of one or more receiving antennas, placed in what is sometimes defined as the "ob- servation domain". Starting from the measured values of the scattering field, it is possible to reconstruct the fundamental properties of the test object by solving an inverse electromagnetic scattering problem.
As it is well known, the inverse problem is non-linear and strongly ill-posed, unless specific approximations are used, which can be applied in specific situations.
In several cases, two-dimensional configurations (2D) can be assumed, i.e., the inspected target has a cylindrical shape, at least as a first approximation. More- over, often the target is illuminated by antennas capable of generating a transverse magnetic (TM) electromagnetic field [25]. These assumptions reduces the problem from a vector and three-dimensional problem to a 2D and scalar one, since it turns out that the only significant the field components are those co-polarized with the incident wave and directed along to the cylinder axis.
In recent years, several methods and algorithms that allow an efficient resolution of the equations of electromagnetic inverse scattering problem have been developed. The proposed approaches can be mainly grouped into two categories: qualitative and quantitative techniques. Qualitative procedures, such as the delay-and-sum technique [26], the linear sampling method [27], and the orthogonality sampling method [28], usually provides reconstructions that allows to extract only some parameters of the targets, such as position, dimensions and shape. However, they are in most cases fast and computationally efficient.On the contrary, quantitative methods allows in principle to retrieve the full distributions of the dielectric properties of the object under test, which allows to also obtain additional information on the materials composing the inspected scenario. Such approaches are often computationally very demanding [25].
Qualitative and quantitative approaches can be combined in order to develop hybrid algorithms [29], [30], [31], [32], [33], [34]. An example is represented by the combination of a delay-and-sum qualitative focusing technique [35], [36], [37] with a quantitative Newton scheme performing a regularization in the framework of the Lp Banach spaces [38], [39], [40].
Holographic microwave imaging techniques are other important qualitative meth- ods. In this case, the processing of data is performed by using through direct and inverse Fourier transforms in order to obtain a map of the inspected target.
As previously mentioned, quantitative approaches aim at retrieving the distributions of the dielectric properties of the scene under test, although they can be significantly more time-consuming especially in 3D imaging. Among them, Newton- type approach are often considered [39], [40].
Recently, artificial neural networks (ANNs) have been considered as powerful tools for quantitative MWI. The first proposed ANNs were developed as shallow network architectures, in which one or at least two hidden layers were considered [41], [42]. Successively, deep neural networks have been proposed, in which more complex fully-connected architecture are adopted. In this framework, Convolutional Neural Networks (CNNs) have been developed as more complex topologies, for classification problems or for solving the inverse scattering problems [43], [44], [45], [46], [47], [48], [49]. In the inverse scattering problems, the CNNs often require a preliminary image retrieved by other techniques [43], [44], [47], [50], [51] and do not allow directly inver- sion from the scattered electric fields collected by the receiving antennas. Standard CNNs are developed for different applications. Examples are represented by Unet [52], ResNet [53] and VGG [54].
This Thesis is devoted to the application of MWI techniques to inspect the human neck. Several pathologic conditions can affect this part of the body, and a non-invasive and nonionizing imaging method can be useful for monitoring patients. The first pathological condition studied in this Thesis is the cervical myelopathy [55], which is a disease that damages the first part of the spinal cord, between the C3 and C7 cervical vertebrae located near the head [56].
The spinal cord has an important function in the body, since it represents the principal actor in the nervous system. For this reason, it is "protected" inside the spinal canal [57]. A first effect of cervical myelopathy is a reduction of the spinal canal sagittal diameter, which may be caused by different factors [58]. Some patients are asymptomatic and for this reason a continuous monitoring could be very helpful for evaluating the pathology progression. To this end, the application of qualitative and quantitative MWI approaches are proposed in this document.
The second neck pathology studied in this Thesis is the neck tumor, in particular supraglottic laryngeal carcinoma [59], thyroid cancer [60] and cervical lymph node metastases [61]. These kinds of tumors are frequently occurring and shown a 50% 5-year survival probability [61],[62], [63], [64]. Fully-connected neural network are proposed for neck tumor detection.
The Thesis is organized as follows. In Chapter 2, the relevant concepts of the electromagnetic theory are recalled. Chapter 3 describes the developed inversion algorithms. It also reports an extensive validation considering both synthetic and experimental data. Detailed data about the imaging approach based on machine
learning are provided in Chapter 4. This chapter also reports the results obtained in a set of simulations and experiments. Finally, some conclusions are drawn in Chapter 5.
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Wintz, Timothée. "Super-resolution in wave imaging." Thesis, Paris Sciences et Lettres (ComUE), 2017. http://www.theses.fr/2017PSLEE052/document.
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Les différentes modalités d’imagerie par ondes présentent chacune des limitations en termes de résolution ou de contraste. Dans ce travail, nous modélisons l’imagerie ultrasonore ultrarapide et présentons des méthodes de reconstruction qui améliorent la précision de l’imagerie ultrasonore. Nous introduisons deux méthodes qui permettent d’augmenter le contraste et de mesurer la position super-résolue et la vitesse dans les vaisseaux sanguins. Nous présentons aussi une méthode de reconstruction des paramètres microscopiques en tomographie d’impédance électrique en utilisant des mesures multifréquence et en s’aidant de la théorie de l’homogénéisationDifferent modalities in wave imaging each present limitations in terms of resolution or contrast. In this work, we present a mathematical model of the ultrafast ultrasound imaging modality and reconstruction methods which can improve contrast and resolution in ultrasonic imaging. We introduce two methods which allow to improve contrast and to locate blood vessels belowthe diffraction limit while simultaneously estimating the blood velocity. We also present a reconstruction method in electrical impedance tomography which allows reconstruction of microscopic parameters from multi-frequency measurements using the theory of homogenization
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Alfowzan, Mohammed Fowzan, and Mohammed Fowzan Alfowzan. "Solutions to Space-Time Inverse Problems." Diss., The University of Arizona, 2016. http://hdl.handle.net/10150/621791.
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Two inverse problems are investigated in this dissertation, taking into account both the spatial and temporal aspects. The first problem addresses the under determined image reconstruction problem for dynamic SPECT. The quality of the reconstructed image is often limited due to having fewer observations than the number of voxels. The proposed algorithms make use of the generalized α-divergence function to improve the estimation performance. The first algorithm is based on an alternating minimization framework to minimize a regularized α-divergence objective function. We demonstrate that selecting an adaptive α policy depending on the time evolution of the voxels gives better performance than a fixed α assignment. The second algorithm is based on Newton's method. A regularized approach has been taken to avoid stability issues. Newton's method is generally computationally demanding due to the complexity associated with inverting the Hessian matrix. A fast Newton-based method is proposed using majorization-minimization techniques that diagonalize the Hessian matrix. In dynamically evolving systems, the prediction matrix plays an important role in the estimation process. An estimation technique is proposed to estimate the prediction matrix using the α-divergence function. The simulation results show that our algorithms provide better performance than the techniques based on the Kullback-Leibler distance. The second problem is the recovery of data transmitted over free-space optical communication channels using orbital angular momentum (OAM). In the presence of atmospheric turbulence, crosstalk occurs among OAM optical modes resulting in an error floor at a relatively high bit error rate. The modulation format considered for the underlying problem is Q-ary pulse position modulation (PPM). We propose and evaluate three joint detection strategies to overcome the OAM crosstalk problem: i) maximum likelihood sequence estimation (MLSE). ii) Q-PPM factor graph detection. iii) branch-and-bound detection. We compare the complexity and the bit-error-rate performance of these strategies in realistic scenarios.
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HE, YUN. "Multiscale Signal Processing and Shape Analysis for an Inverse SAR Imaging System." NCSU, 2001. http://www.lib.ncsu.edu/theses/available/etd-20010704-160913.
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The great challenge in signal processing is to devise computationally efficient and statistically optimal algorithms for estimating signals from noisy background and understanding their contents. This thesis treats the problem of multiscale signal processing and shape analysis for an Inverse Synthetic Aperture Radar (ISAR) imaging system. To address some of the limitations of conventional techniques in radar image processing, an information theoretic approach for target motion estimation is first proposed. A wavelet based multiscale method for shape enhancement is subsequently derived and followed by a regression technique for shape recognition.Building on entropy-based divergence measures which have shown promising results in many areas of engineering and image processing, we introduce in this thesis a new generalized divergence measure, namely the Jensen-Rényi divergence. Upon establishing its properties such as convexity and its upper bound etc., we apply it to image registration for ISAR focusing as well as related problems in data fusion. Attempting to extend current approaches to signal estimation in a wavelet framework, which have generally relied on the assumption of normally distributed perturbations, we propose a novel non-linear filtering technique, as a pre-processing step for the shapes obtained from an ISAR imaging system. The key idea is to project a noisy shape onto a wavelet domain and to suppress wavelet coefficients by a mask derived from curvature extrema in its scale space representation. For a piecewise smooth signal, it can be shown that filtering by this curvature mask is equivalent to preserving the signal pointwise Hölder exponents at the singular points, and to lifting its smoothness at all the remaining points. To identify a shape independently of its registration information, we propose matching two configurations by regression, using notations of general shape spaces and procrustean distances. In particular, we study the generalized matching by estimating mean shapes in two dimensions. Simulation results show that matching by way of a mean shape is more robust than matching target shapes directly.
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Steenman, Daryl G. "Investigation of near-field electromagnetic source imaging using inverse Green's function integrations." Thesis, Monterey, California: Naval Postgraduate School, 1999. http://hdl.handle.net/10945/13643.
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As continued efforts are made to reduce the radar cross sections of aircraft and ships, designs are first modeled with computers and then tested in the lab. In the far-field of these tested objects, actual sources of high reflectivity or "Hot Spots" on the tested objects can be isolated to within only one half the wavelength of the electromagnetic wave used for testing. Ideally, a probe could measure fields on the surface of the object being tested to completely isolate the source of the hot spot. Unfortunately, the presence of the probe on the surface of the object will disturb the very fields it is attempting to measure. Probe measurements made in the near field, close to but not on the object, can be designed to reduce the influence of the probe while providing accurate field data. The data thus measured, while not able to determine the source location perfectly, can be used to localize a source to less than one half wavelength, the far-field diffraction limit .This thesis tests a technique for back propagating computer generated near field measurements of an axisymmetric field source to determine the fields closer to the source. Several cases are examined that test the accuracy and resolving capability of the technique.
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COLANGELI, CLAUDIO. "Clustering Inverse Beamforming and multi-domain acoustic imaging approaches for vehicles NVH." Doctoral thesis, Università Politecnica delle Marche, 2017. http://hdl.handle.net/11566/245537.
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Il rumore percepito all’interno della cabina di un veicolo è un aspetto molto rilevante nella valutazione della sua qualità complessiva. Metodi sperimentali di acoustic imaging, quali beamforming e olografia acustica, sono usati per identificare le principali sorgenti che contribuiscono alla rumorosità percepita all’interno del veicolo. L’obiettivo della tesi proposta è di fornire strumenti per effettuare dettagliate analisi quantitative tramite tali tecniche, ad oggi relegate alle fasi di studio preliminare, proponendo un approccio modulare che si avvale di analisi dei fenomeni vibro-acustici nel dominio della frequenza, del tempo e dell’angolo di rotazione degli elementi rotanti tipicamente presenti in un veicolo. Ciò permette di ridurre tempi e costi della progettazione, garantendo, al contempo, una maggiore qualità del pacchetto vibro-acustico. L’innovativo paradigma proposto prevede l’uso combinato di algoritmi di pre- e post- processing con tecniche inverse di acoustic imaging per lo studio di rilevanti problematiche quali l’identificazione di sorgenti sonore esterne o interne all’abitacolo e del rumore prodotto da dispositivi rotanti. Principale elemento innovativo della tesi è la tecnica denominata Clustering Inverse Beamforming. Essa si basa su un approccio statistico che permette di incrementare l’accuratezza (range dinamico, localizzazione e quantificazione) di una immagine acustica tramite la combinazione di soluzioni, del medesimo problema inverso, ottenute considerando diversi sotto-campioni dell’informazione sperimentale disponibile, variando, in questo modo, in maniera casuale la sua formulazione matematica. Tale procedimento garantisce la ricostruzione nel dominio della frequenza e del tempo delle sorgenti sonore identificate. Un metodo innovativo è stato inoltre proposto per la ricostruzione, ove necessario, di sorgenti sonore nel dominio dell’angolo. I metodi proposti sono stati supportati da argomentazioni teoriche e validazioni sperimentali su scala accademica e industriale.The interior sound perceived in vehicle cabins is a very important attribute for the user. Experimental acoustic imaging methods such as beamforming and Near-field Acoustic Holography are used in vehicles noise and vibration studies because they are capable of identifying the noise sources contributing to the overall noise perceived inside the cabin. However these techniques are often relegated to the troubleshooting phase, thus requiring additional experiments for more detailed NVH analyses. It is therefore desirable that such methods evolve towards more refined solutions capable of providing a larger and more detailed information. This thesis proposes a modular and multi-domain approach involving direct and inverse acoustic imaging techniques for providing quantitative and accurate results in frequency, time and angle domain, thus targeting three relevant types of problems in vehicles NVH: identification of exterior sources affecting interior noise, interior noise source identification, analysis of noise sources produced by rotating machines. The core finding of this thesis is represented by a novel inverse acoustic imaging method named Clustering Inverse Beamforming (CIB). The method grounds on a statistical processing based on an Equivalent Source Method formulation. In this way, an accurate localization, a reliable ranking of the identified sources in frequency domain and their separation into uncorrelated phenomena is obtained. CIB is also exploited in this work for allowing the reconstruction of the time evolution of the sources sought. Finally a methodology for decomposing the acoustic image of the sound field generated by a rotating machine as a function of the angular evolution of the machine shaft is proposed. This set of findings aims at contributing to the advent of a new paradigm of acoustic imaging applications in vehicles NVH, supporting all the stages of the vehicle design with time-saving and cost-efficient experimental techniques. The proposed innovative approaches are validated on several simulated and real experiments.
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Pereira, Antonio. "Acoustic imaging in enclosed spaces." Thesis, Lyon, INSA, 2013. http://www.theses.fr/2013ISAL0066/document.
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Ce travail de recherche porte sur le problème de l'identification des sources de bruit en espace clos. La motivation principale était de proposer une technique capable de localiser et quantifier les sources de bruit à l'intérieur des véhicules industriels, d'une manière efficace en temps. Dans cette optique, la méthode pourrait être utilisée par les industriels à des fins de réduction de bruit, et donc construire des véhicules plus silencieux. Un modèle simplifié basé sur la formulation par sources équivalentes a été utilisé pour résoudre le problème. Nous montrerons que le problème est mal conditionné, dans le sens où il est très sensible face aux erreurs de mesure, et donc des techniques dites de régularisation sont nécessaires. Une étude détaillée de cette question, en particulier le réglage de ce qu'on appelle de paramètre de régularisation, a été important pour assurer la stabilité de la solution. En particulier, un critère de régularisation basé sur une approche bayésienne s'est montré très robuste pour ajuster le paramètre de régularisation de manière optimale. L'application cible concernant des environnements intérieurs relativement grands, nous a imposé des difficultés supplémentaires, à savoir: (a) le positionnement de l'antenne de capteurs à l'intérieur de l'espace; (b) le nombre d'inconnues (sources potentielles) beaucoup plus important que le nombre de positions de mesure. Une formulation par pondération itérative a ensuite été proposé pour surmonter les problèmes ci-dessus de manière à: (1) corriger pour le positionnement de l'antenne de capteurs dans l'habitacle ; (2) obtenir des résultats corrects en terme de quantification des sources identifiées. Par ailleurs, l'approche itérative nous a conduit à des résultats avec une meilleure résolution spatiale ainsi qu'une meilleure dynamique. Plusieurs études numériques ont été réalisées afin de valider la méthode ainsi que d'évaluer sa sensibilité face aux erreurs de modèle. En particulier, nous avons montré que l'approche est affectée par des conditions non-anéchoïques, dans le sens où les réflexions sont identifiées comme des vraies sources. Une technique de post-traitement qui permet de distinguer entre les chemins directs et réverbérants a été étudiée. La dernière partie de cette thèse porte sur des validations expérimentales et applications pratiques de la méthode. Une antenne sphérique constituée d'une sphère rigide et 31 microphones a été construite pour les tests expérimentaux. Plusieurs validations académiques ont été réalisées dans des environnements semi-anéchoïques, et nous ont illustré les avantages et limites de la méthode. Enfin, l'approche a été testé dans une application pratique, qui a consisté à identifier les sources de bruit ou faiblesses acoustiques à l'intérieur d'un busThis thesis is concerned with the problem of noise source identification in closed spaces. The main motivation was to propose a technique which allows to locate and quantify noise sources within industrial vehicles, in a time-effective manner. In turn, the technique might be used by manufacturers for noise abatement purposes such as to provide quieter vehicles. A simplified model based on the equivalent source formulation was used to tackle the problem. It was shown that the problem is ill-conditioned, in the sense that it is very sensitive to errors in measurement data, thus regularization techniques were required. A detailed study of this issue, in particular the tuning of the so-called regularization parameter, was of importance to ensure the stability of the solution. In particular, a Bayesian regularization criterion was shown to be a very robust approach to optimally adjust the regularization parameter in an automated way. The target application concerns very large interior environments, which imposes additional difficulties, namely: (a) the positioning of the measurement array inside the enclosure; (b) a number of unknowns ("candidate" sources) much larger than the number of measurement positions. An iterative weighted formulation was then proposed to overcome the above issues by: first correct for the positioning of the array within the enclosure and second iteratively solve the problem in order to obtain a correct source quantification. In addition, the iterative approach has provided results with an enhanced spatial resolution and dynamic range. Several numerical studies have been carried out to validate the method as well as to evaluate its sensitivity to modeling errors. In particular, it was shown that the approach is affected by non-anechoic conditions, in the sense that reflections are identified as "real" sources. A post-processing technique which helps to distinguish between direct and reverberant paths has been discussed. The last part of the thesis was concerned with experimental validations and practical applications of the method. A custom spherical array consisting of a rigid sphere and 31 microphones has been built for the experimental tests. Several academic experimental validations have been carried out in semi-anechoic environments, which illustrated the advantages and limits of the method. Finally, the approach was tested in a practical application, which consisted in identifying noise sources inside a bus at driving conditions
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Lim, Kian Guan. "Battle damage assessment using inverse synthetic aperture radar (ISAR)." Thesis, Monterey, California. Naval Postgraduate School, 2004. http://hdl.handle.net/10945/1223.
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Approved for public release; distribution in unlimited.An imaging radar, like ISAR, offers a combatant the capability to perform long range surveillance with high quality imagery for positive target identification. Extending this attractive feature to the battle damage assessment problem (BDA) gives the operator instant viewing of the target's behavior when it is hit. As a consequence, immediate and decisive action can be quickly taken (if required). However, the conventional Fourier processing adopted by most ISAR systems does not provide adequate time resolution to capture the target's dynamic responses during the hit. As a result, the radar image becomes distorted. To improve the time resolution, time-frequency transform (TFT) methods of ISAR imaging have been proposed. Unlike traditional Fourier-based processing, TFT's allows variable time resolution of the entire event that falls within the ISAR coherent integration period to be extracted as part of the imaging process. We have shown in this thesis that the use of linear Short Time-Frequency Transforms allows the translational response of the aircraft caused by a blast force to be clearly extracted. The TFT extracted images not only tell us how the aircraft responds to a blast effect but also provides additional information about the cause of image distortion in the traditional ISAR display.
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Burvall, Anna. "Axicon imaging by scalar diffraction theory." Doctoral thesis, KTH, Microelectronics and Information Technology, IMIT, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3736.
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Axicons are optical elements that produce Bessel beams,i.e., long and narrow focal lines along the optical axis. Thenarrow focus makes them useful ine.g. alignment, harmonicgeneration, and atom trapping, and they are also used toincrease the longitudinal range of applications such astriangulation, light sectioning, and optical coherencetomography. In this thesis, axicons are designed andcharacterized for different kinds of illumination, using thestationary-phase and the communication-modes methods.
The inverse problem of axicon design for partially coherentlight is addressed. A design relation, applicable toSchell-model sources, is derived from the Fresnel diffractionintegral, simplified by the method of stationary phase. Thisapproach both clarifies the old design method for coherentlight, which was derived using energy conservation in raybundles, and extends it to the domain of partial coherence. Thedesign rule applies to light from such multimode emitters aslight-emitting diodes, excimer lasers and some laser diodes,which can be represented as Gaussian Schell-model sources.
Characterization of axicons in coherent, obliqueillumination is performed using the method of stationary phase.It is shown that in inclined illumination the focal shapechanges from the narrow Bessel distribution to a broadasteroid-shaped focus. It is proven that an axicon ofelliptical shape will compensate for this deformation. Theseresults, which are all confirmed both numerically andexperimentally, open possibilities for using axicons inscanning optical systems to increase resolution and depthrange.
Axicons are normally manufactured as refractive cones or ascircular diffractive gratings. They can also be constructedfrom ordinary spherical surfaces, using the sphericalaberration to create the long focal line. In this dissertation,a simple lens axicon consisting of a cemented doublet isdesigned, manufactured, and tested. The advantage of the lensaxicon is that it is easily manufactured.
The longitudinal resolution of the axicon varies. The methodof communication modes, earlier used for analysis ofinformation content for e.g. line or square apertures, isapplied to the axicon geometry and yields an expression for thelongitudinal resolution. The method, which is based on abi-orthogonal expansion of the Green function in the Fresneldiffraction integral, also gives the number of degrees offreedom, or the number of information channels available, forthe axicon geometry.
Keywords:axicons, diffractive optics, coherence,asymptotic methods, communication modes, information content,inverse problems
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Poonawala, Amyn. "Mask design for single and double exposure optical microlithography : an inverse imaging approach /." Diss., Digital Dissertations Database. Restricted to UC campuses, 2007. http://uclibs.org/PID/11984.
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Shang, Xuefeng Ph D. Massachusetts Institute of Technology. "Inverse scattering : theory and application to the imaging of the Earth's seismic discontinuities." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/87511.
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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Earth, Atmospheric, and Planetary Sciences, 2014.Cataloged from PDF version of thesis.
Includes bibliographical references.
In this thesis we further develop concepts in inverse scattering, which enable higher resolution imaging with data from dense networks and arrays. We apply the new methods to studies of the crust beneath south Tibet and the core-mantle boundary (CMB) region beneath Central America and East Asia. First, we develop a new method, which we call passive source reverse time migration (RTM), for subsurface imaging with teleseismic array data. Multi-component array data are first propagated backward by solving the elastic wave equation. After polarization separation, a modified cross-correlation imaging condition between P and S wave constitutes is applied to obtain an inverse scattering transform. From synthetic experiments it is evident that for complex geological structures RTM is superior to traditional receiver functions analysis, such as common conversion point (CCP) stacking. Two preprocessing steps are required for RTM application on sparsely sampled teleseismic dataset: source normalization and trace interpolation. The source radiation pattern, especially the polarity of traces, is corrected by multi-channel cross-correlation technique. The unknown source signature is then estimated by principle component analysis and deconvolved from raw data by Wiener deconvolution. Curvelet interpolation with sparsity promotion is employed to interpolate irregularly and sparsely sampled traces into regular and dense grids. Synthetic and real data examples demonstrate that for typical teleseismic acquisition geometry, with 50% to 85% missing traces, the curvelet-based interpolation works remarkably well. The application on Hi-CLIMB array data in Tibetan plateau reveals clear and continuous Moho discontinuity at the depth of about 70 km, as well as fine crustal structures. Second, we use a high-frequency approximation of inverse scattering, generalized Radon transform (GRT), to probe the lowermost mantle beneath Central America and East Asia. Inverse scattering of about 130,000 ScS traces and 120,000 SKKS traces reveals multiple reflectors above the conventional D" region. This result is inconsistent with expectations from a pure thermal response of a single isochemical post-perovskite transition but can be explained with post-perovskite transitions in differentiated slab materials. Our results imply that the lowennost mantle is more complex than hitherto thought and that the presence of interfaces and compositional heterogeneity beyond the D" region.
by Xuefeng Shang.
Ph. D.
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Fouda, Ahmed Elsayed. "Electromagnetic Time-Reversal Imaging and Tracking Techniques for Inverse Scattering and Wireless Communications." The Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1366202740.
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Chang, Paul Chinling. "Physics-Based Inverse Processing and Multi-path Exploitation for Through-Wall Radar Imaging." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1306646674.
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Camargo, Erick Darío León Bueno de. "Desenvolvimento de algoritmo de imagens absolutas de tomografia por impedância elétrica para uso clínico." Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/3/3152/tde-26062014-205827/.
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A Tomografia de Impedância Elétrica é uma técnica de obtenção de imagens não invasiva que pode ser usada em aplicações clínicas para estimar a impeditividade dos tecidos a partir de medidas elétricas na superfície do corpo. Matematicamente este é um problema inverso, não linear e mal posto. Geralmente é usado um filtro espacial Gaussiano passa alta como método de regularização para resolver o problema inverso. O objetivo principal deste trabalho é propor o uso de informação estatística fisiológica e anatômica da distribuição de resistividades dos tecidos do tórax, também chamada de atlas anatômico, em conjunto com o filtro Gaussiano como métodos de regularização. A metodologia proposta usa o método dos elementos finitos e o algoritmo de Gauss-Newton para reconstruir imagens de resistividade tridimensionais. A Teoria do Erro de Aproximação é utilizada para reduzir os erros relacionados à discretização e dimensões da malha de elementos finitos. Dados de tomografia de impedância elétrica e imagens de tomografia computadorizada coletados in vivo em um suíno com diferentes alterações fisiológicas pulmonares foram utilizados para validar o algoritmo proposto. As imagens obtidas foram consistentes com os fenômenos de atelectasia, derrame pleural, pneumotórax e variações associadas a diferentes níveis de pressão durante a ventilação mecânica. Os resultados mostram que a reconstrução de imagens de suínos com informação clínica significativa é possível quando tanto o filtro Gaussiano quanto o atlas anatômico são usados como métodos de regularização.Electrical Impedance Tomography is a non invasive imaging technique that can be used in clinical applications to infer living tissue impeditivity from boundary electrical measurements. Mathematically this is an non-linear ill-posed inverse problem. Usually a spatial high-pass Gaussian filter is used as a regularization method for solving the inverse problem. The main objective of this work is to propose the use of physiological and anatomical priors of tissue resistivity distribution within the thorax, also known as anatomical atlas, in conjunction with the Gaussian filter as regularization methods. The proposed methodology employs the finite element method and the Gauss-Newton algorithm in order to reconstruct three-dimensional resistivity images. The Approximation Error Theory is used to reduce discretization effects and mesh size errors. Electrical impedance tomography data and computed tomography images of physiological pulmonary changes collected in vivo in a swine were used to validate the proposed method. The images obtained are compatible with atelectasis, pneumothorax, pleural effusion and different ventilation pressures during mechanical ventilation. The results show that image reconstruction from swines with clinically significant information is feasible when both the Gaussian filter and the anatomical atlas are used as regularization methods.
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Yin, Ke. "New algorithms for solving inverse source problems in imaging techniques with applications in fluorescence tomography." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/48945.
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This thesis is devoted to solving the inverse source problem arising in image reconstruction problems. In general, the solution is non-unique and the problem is severely ill-posed. Therefore, small perturbations, such as the noise in the data, and the modeling error in the forward problem, will cause huge errors in the computations. In practice, the most widely used method to tackle the problem is based on Tikhonov-type regularizations, which minimizes a cost function combining a regularization term and a data fitting term. However, because the two tasks, namely regularization and data fitting, are coupled together in Tikhonov regularization, they are difficult to solve. It happens even if each task can be efficiently solved when they are separate.
We propose a method to overcome the major difficulties, namely the non-uniqueness of the solution and noisy data fitting, separately. First we find a particular solution called the orthogonal solution that satisfies the data fitting term. Then we add to it a correction function in the kernel space so that the final solution fulfills the regularization and other physical requirements. The key idea is that the correction function in the kernel has no impact to the data fitting, and the regularization is imposed in a smaller space. Moreover, there is no parameter needed to balance the data fitting and regularization terms. As a case study, we apply the proposed method to Fluorescence Tomography (FT), an emerging imaging technique well known for its ill-posedness and low image resolution in existing reconstruction techniques. We demonstrate by theory and examples that the proposed algorithm can drastically improve the computation speed and the image resolution over existing methods.
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Petrović, Nikola. "Measurement System for Microwave Imaging Towards a Biomedical Application." Doctoral thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-24878.
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Microwave imaging techniques have shown excellent capabilities in various fields such as civil engineering, nondestructive testing, industrial applications, and have in recent decades experienced strong growth as a research topic in biomedical diagnostics. Many research groups throughout the world work on prototype systems for producing images of human tissues in different biomedical applications, particularly breast tumor detection. However, the research community faces many challenges and in order to be competitive to other imaging modalities one of the means is to put emphasis on experimental work. Consequently, the use of flexible and accurate measurement systems, together with the design and fabrication of suitable antennas, are essential to the development of efficient microwave imaging systems. The first part of this thesis focuses on measurement systems for microwave imaging in terms of antenna design and development, robot controlled synthetic array geometries, permittivity measurements, and calibration. The aim was to investigate the feasibility of a flexible system for measuring the fields around an inhomogeneous object and to create quantitative images. Hence, such an aim requires solving of a nonlinear inverse scattering problem, which in turn requires accurate measurements for producing good quality experimental data. The presented solution by design of a flexible measurement system is validated by examination of microwave imaging from experimental data with a breast phantom. The second part of the thesis deals with the research challenges of designing high performance antennas to be placed in direct contact with or in close proximity to the imaged object. The need for novel antenna applicators is envisaged in the framework of the Mamacell measurement system, where the antenna applicators have to be designed and constructed to effectively couple the energy into the imaging object. For this purpose the main constraints and design requirements are a narrow lobe of the antenna, very small near-field effects, and small size. Numerical simulations and modeling shows that the proposed ridged waveguide antenna is capable of fulfilling the design requirements and the performance goals, demonstrating the potential for the future microwave imaging system called Mamacell.
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Moffitt, Michael Adam. "Functional Imaging of the Mammalian Spinal Cord." Case Western Reserve University School of Graduate Studies / OhioLINK, 2004. http://rave.ohiolink.edu/etdc/view?acc_num=case1081363883.
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Zhang, Yu. "Inverse opal scaffolds and photoacoustic microscopy for regenerative medicine." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/50231.
Full textAbstract:
This research centers on the fabrication, characterization, and engineering of inverse
opal scaffolds, a novel class of three-dimensional (3D) porous scaffolds made of
biocompatible and biodegradable polymers, for applications in tissue engineering and
regenerative medicine. The unique features of an inverse opal scaffold include a highly
ordered array of pores, uniform and finely tunable pore sizes, high interconnectivity, and
great reproducibility.
The first part of this work focuses on the fabrication and functionalization of inverse
opal scaffolds based on poly(D,L-lactic-co-glycolic acid) (PLGA), a biodegradable
material approved by the U.S. Food and Drug Administration (FDA). The advantages of
the PLGA inverse opal scaffolds are also demonstrated by comparing with their
counterparts with spherical but non-uniform pores and poor interconnectivity.
The second part of this work shows two examples where the PLGA inverse opal
scaffolds were successfully used as a well-defined system to investigate the effect of pore
size of a 3D porous scaffold on the behavior of cell and tissue growth. Specifically, I
have demonstrated that i) the differentiation of progenitor cells in vitro was dependent on
the pore size of PLGA-based scaffolds and the behavior of the cells was determined by
the size of individual pores where the cells resided in, and ii) the neovascularization
process in vivo could be directly manipulated by controlling a combination of pore and
window sizes when they were applied to a mouse model.
The last part of this work deals with the novel application of photoacoustic
microscopy (PAM), a volumetric imaging modality recently developed, to tissue
engineering and regenerative medicine, in the context of non-invasive imaging and
quantification of cells and tissues grown in PLGA inverse opal scaffolds, both in vitro
and in vivo. Furthermore, the capability of PAM to monitor and quantitatively analyze
the degradation of the scaffolds themselves was also demonstrated.
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Hugelier, Siewert. "Approaches to inverse problems in chemical imaging : applications in super-resolution and spectral unmixing." Thesis, Lille 1, 2017. http://www.theses.fr/2017LIL10144/document.
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L’imagerie chimique permet d’accéder à la distribution spatiale des espèces chimiques. Nous distinguerons dans cette thèse deux types d’images différents: les images spatiales-temporelles et les images spatiales-spectrales.La microscopie de fluorescence super-résolue a commencé avec un faible nombre de fluorophores actifs par image. Actuellement, ça a évolué vers l’imagerie en haute densité qui requiert de nouvelles façons d’analyse. Nous proposons SPIDER, une approche de déconvolution par moindres carrés pénalisés. La considération de plusieurs pénalités permet de traduire les propriétés des émetteurs utilisés dans l'imagerie de fluorescence super-résolue. L'utilisation de cette méthode permet d'étudier des changements structuraux et morphologiques dans les échantillons biologiques. La méthode a été appliquée à l’imagerie sur cellules vivantes d’une cellule HEK-293T encodée par la protéine fluorescente DAKAP-Dronpa. On a pu obtenir une résolution spatiale de 55nm pour un temps d’acquisition de 0.5s.La résolution d'images hyperspectrales avec MCR-ALS fournit des informations spatiales et spectrales des contributions individuelles dans le mélange. Néanmoins, le voisinage des pixels est perdu du fait du dépliement du cube de données hyperspectrales sous forme d’une matrice bidirectionnelle. L’implémentation de contraintes spatiales n’est donc pas possible en MCR-ALS. Nous proposons une approche alternative dans laquelle une étape de repliement/dépliement est effectuée à chaque itération qui permet d’ajouter des fonctionnalités spatiales globales à la palette des contraintes. Nous avons développé plusieurs contraintes et on montre leur application aux données expérimentalesBesides the chemical information, chemical imaging also offers insights in the spatial distribution of the samples. Within this thesis, we distinguish between two different types of images: spatial-temporal images (super-resolution fluorescence microscopy) and spatial-spectral images (unmixing). In early super-resolution fluorescence microscopy, a low number of fluorophores were active per image. Currently, the field evolves towards high-density imaging that requires new ways of analysis. We propose SPIDER, an image deconvolution approach with multiple penalties. These penalties directly translate the properties of the blinking emitters used in super-resolution fluorescence microscopy imaging. SPIDER allows investigating highly dynamic structural and morphological changes in biological samples with a high fluorophore density. We applied the method on live-cell imaging of a HEK-293T cell labeled with DAKAP-Dronpa and demonstrated a spatial resolution down to 55 nm and a time sampling of 0.5 s. Unmixing hyperspectral images with MCR-ALS provides spatial and spectral information of the individual contributions in the mixture. Due to loss of the pixel neighborhood during the unfolding of the hyperspectral data cube to a two-way matrix, spatial information cannot be added as a constraint during the analysis We therefore propose an alternative approach in which an additional refolding/unfolding step is performed in each iteration. This data manipulation allows global spatial features to be added to the palette of MCR-ALS constraints. From this idea, we also developed several constraints and show their application on experimental data
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Henriksson, Tommy. "CONTRIBUTION TO QUANTITATIVE MICROWAVE IMAGING TECHNIQUES FOR BIOMEDICAL APPLICATIONS." Doctoral thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-5882.
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This dissertation presents a contribution to quantitative microwave imaging for breast tumor detection. The study made in the frame of a joint supervision Ph.D. thesis between University Paris-SUD 11 (France) and Mälardalen University (Sweden), has been conducted through two experimental microwave imaging setups, the existing 2.45 GHz planar camera (France) and the multi-frequency flexible robotic system, (Sweden), under development. In this context a 2D scalar flexible numerical tool based on a Newton-Kantorovich (NK) scheme, has been developed. Quantitative microwave imaging is a three dimensional vectorial nonlinear inverse scattering problem, where the complex permittivity of an object is reconstructed from the measured scattered field, produced by the object. The NK scheme is used in order to deal with the nonlinearity and the ill-posed nature of this problem. A TM polarization and a two dimensional medium configuration have been considered in order to avoid its vectorial aspect. The solution is found iteratively by minimizing the square norm of the error with respect to the scattered field data. Consequently, the convergence of such iterative process requires, at least two conditions. First, an efficient calibration of the experimental system has to be associated to the minimization of model errors. Second, the mean square difference of the scattered field introduced by the presence of the tumor has to be large enough, according to the sensitivity of the imaging system. The existing planar camera associated to a flexible 2D scalar NK code, are considered as an experimental platform for quantitative breast imaging. A preliminary numerical study shows that the multi-view planar system is quite efficient for realistic breast tumor phantoms, according to its characteristics (frequency, planar geometry and water as a coupling medium), as long as realistic noisy data are considered. Furthermore, a multi-incidence planar system, more appropriate in term of antenna-array arrangement, is proposed and its concept is numerically validated. On the other hand, an experimental work which includes a new fluid-mixture for the realization of a narrow band cylindrical breast phantom, a deep investigation in the calibration process and model error minimization, is presented. This conducts to the first quantitative reconstruction of a realistic breast phantom by using multi-view data from the planar camera. Next, both the qualitative and quantitative reconstruction of 3D inclusions into the cylindrical breast phantom, by using data from all the retina, are shown and discussed. Finally, the extended work towards the flexible robotic system is presented.A dissertation prepared through an international convention for a joint supervision thesis with Université Paris-SUD 11, France
Microwaves in biomedicine
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Hislop, Gregory Francis. "Diffraction Tomographic Imaging of Shallowly Buried Targets using Ground Penetrating Radar." Thesis, Queensland University of Technology, 2005. https://eprints.qut.edu.au/16125/1/Gregory_Hislop_Thesis.pdf.
Full textAbstract:
The problem of subsurface imaging with Ground Penetrating Radar (GPR) is a challenging one. Due to the low-pass nature of soil sensors must utilise wave-lengths that are of the same order of magnitude as the object being imaged. This makes imaging difficult as straight ray approximations commonly used in higher frequency applications cannot be used. The problem becomes even more challenging when the target is shallowly buried as in this case the ground surface reflection and the near-field parameters of the radar need to be considered. This thesis has investigated the problem of imaging shallowly buried targets with GPR. Two distinct problems exist in this field radar design and the design of inverse scattering techniques. This thesis focuses on the design of inverse scattering techniques capable of taking the electric field measurements from the receiver and providing accurate images of the scatterer in real time.
The thesis commences with a brief introduction to GPR theory. It then provides an extensive review of linear inverse scattering techniques applied to raw GPR data. As a result of this review the thesis draws the conclusion that, due to its strong foundations in Maxwell's equations, diffraction tomography is the most appropriate approach for imaging shallowly buried targets with GPR. A three-dimensional diffraction tomographic technique is then developed. This algorithm forms the primary contribution of the thesis.
The novel diffraction tomography technique improves on its predecessors by catering for shallowly buried targets, significant antenna heights and evanescent waves. This is also the first diffraction tomography technique to be derived for a range of antenna structures. The advantages of the novel technique are demonstrated first mathematically then on synthetic and finally practical data. The algorithm is shown to be of high practical value by producing accurate images of buried targets in real time.
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Hislop, Gregory Francis. "Diffraction Tomographic Imaging of Shallowly Buried Targets using Ground Penetrating Radar." Queensland University of Technology, 2005. http://eprints.qut.edu.au/16125/.
Full textAbstract:
The problem of subsurface imaging with Ground Penetrating Radar (GPR) is a challenging one. Due to the low-pass nature of soil sensors must utilise wave-lengths that are of the same order of magnitude as the object being imaged. This makes imaging difficult as straight ray approximations commonly used in higher frequency applications cannot be used. The problem becomes even more challenging when the target is shallowly buried as in this case the ground surface reflection and the near-field parameters of the radar need to be considered. This thesis has investigated the problem of imaging shallowly buried targets with GPR. Two distinct problems exist in this field radar design and the design of inverse scattering techniques. This thesis focuses on the design of inverse scattering techniques capable of taking the electric field measurements from the receiver and providing accurate images of the scatterer in real time. The thesis commences with a brief introduction to GPR theory. It then provides an extensive review of linear inverse scattering techniques applied to raw GPR data. As a result of this review the thesis draws the conclusion that, due to its strong foundations in Maxwell's equations, diffraction tomography is the most appropriate approach for imaging shallowly buried targets with GPR. A three-dimensional diffraction tomographic technique is then developed. This algorithm forms the primary contribution of the thesis. The novel diffraction tomography technique improves on its predecessors by catering for shallowly buried targets, significant antenna heights and evanescent waves. This is also the first diffraction tomography technique to be derived for a range of antenna structures. The advantages of the novel technique are demonstrated first mathematically then on synthetic and finally practical data. The algorithm is shown to be of high practical value by producing accurate images of buried targets in real time.
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Dupuy, Clément. "Reconstruction d'image pour l'acousto-optique vers une imagerie quantitative." Thesis, Paris Sciences et Lettres (ComUE), 2017. http://www.theses.fr/2017PSLET034.
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La localisation par la Lumière d’objets millimétriques ou sub-millimétriques dans des milieux épais fortement diffusants de plusieurs centimètres d’épaisseur est un réel challenge dans de nombreux domaines comme par exemple la Sécurité (détection de produits dangereux, détection en environnement hostile), mais aussi à la Biologie et la Médecine (détection de tumeurs, balles, études fonctionnelles, ....). La lumière apporte des informations complémentaires (spécificité, concentration, fonctionnalité) grâce à sa sensibilité spectrale, par exemple dans la fenêtre thérapeutique optique (600-1100nm). Le problème majeur est alors celui lié à la diffusion multiple de la lumière qui empêche toute imagerie conventionnelle. La localisation peut cependant être obtenue en appliquant simultanément une excitation ultrasonore (US), balistique dans ces milieux jusqu’à la dizaine de MHz, et en mesurant la quantité de lumière qui a été marquée par les US suite à l’effet acousto-optique (essentiellement un décalage de fréquence sur la porteuse laser). Cette technique est étudiée sous plusieurs angles par quelques laboratoires dans le monde et notamment de manière expérimentale par une équipe à l’Institut Langevin à Paris et de manière numérique au Laboratoire Medical Physics and Bioengineering, UCL à Londres. L’objectif de ma thèse est de mettre en commun le savoir-faire des deux équipes afin d’obtenir des mesures quantitatives des propriétés optiques locales de milieux diffusantThe optical properties of biological tissues are of significant clinical interest. Such media are highly scattering to the near-infrared light which offers the required contrast, and consequently purely optical approaches to imaging tissues at depth suffer from limited spatial resolution. Acousto-optic imaging is a multi-modal technique which overcomes this problem by combining the optical contrast of near infra-red light with the spatial resolution of ultrasound, permitting millimetre resolution at depths of several centimetres. Raw measurements made using the acousto-optic technique are corrupted by the varying optical fluence in the medium. By using inverse problem base reconstructions algorithms, it is possible to reconstruct a map of the absorption coefficient inside the medium. My PhD is conducted between Institut Langevin, in Paris, where my acousto- optics imaging setup is and the Medical Physics and Bioengineering lab in UCL, in London where I work on the reconstruction algorithms in order to achieve quantitative measurement
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Wei, Hsin-Yu. "Magnetic induction tomography for medical and industrial imaging : hardware and software development." Thesis, University of Bath, 2012. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.558901.
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The main topics of this dissertation are the hardware and the software developments in magnetic induction tomography imaging techniques. In the hardware sections, all the tomography systems developed by the author will be presented and discussed in detail. The developed systems can be divided into two categories, according to the property of the target imaging materials: high conductivity materials and low conductivity materials. Each system has its own suitable application, and each will thus be tested under different circumstances. In terms of the software development, the forward and inverse problems have been studied, including the eddy current problem modeling, sensitivity map formulae derivation and iterative/non-iterative inverse solvers equations. The Biot-Savart Theory was implemented in the ‘two-potential’ method that was used in the eddy current model in order to improve the system’s flexibility. Many different magnetic induction tomography schemes are proposed for the first time in this field of research, their aim being to improve the spatial and temporal resolution of the final reconstructed images. These novel schemes usually involve some modifications of the system hardware and forward/inverse calculations. For example, the rotational scheme can improve the ill-posedness and edge detectability of the system; the volumetric scheme can provide extra spatial resolution in the axial direction; and the temporal scheme can improve the temporal resolution by using the correlation between the consecutive datasets. Volumetric imaging requires an intensive amount of extra computational resources. To overcome the issue of memory constraints when solving large-scale inverse problems, a matrix-free method was proposed, also for the first time in magnetic induction tomography. All the proposed algorithms are verified by the experimental data obtained from suitable tomography systems developed by the author. Although magnetic induction tomography is a new imaging technique, it is believed that the technique is well developed for real-life applications. Several potential applications for magnetic induction tomography are suggested. The initial proof-of-concept study for a challenging low conductivity two-phase flow imaging process is provided. In this thesis, a range of contributions have been made in the field of magnetic induction tomography, which will help the magnetic induction tomography research to be carried on further.
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Sorensen, Thomas J. "Inverse Scattering Image Quality with Noisy Forward Data." Diss., CLICK HERE for online access, 2008. http://contentdm.lib.byu.edu/ETD/image/etd2541.pdf.
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Kumar, Dinesh. "Boundary-constrained inverse consistent image registration and its applications." Diss., University of Iowa, 2011. https://ir.uiowa.edu/etd/1006.
Full textAbstract:
This dissertation presents a new inverse consistent image registration (ICIR) method
called boundary-constrained inverse consistent image registration (BICIR).
ICIR algorithms jointly estimate the
forward and reverse transformations between two images while minimizing
the inverse consistency error (ICE).
The ICE at a point is defined as the distance between
the starting and ending location of a point mapped through the forward
transformation and then the reverse transformation.
The novelty of the BICIR method is that a region of interest (ROI) in one
image is registered with its corresponding ROI. This is accomplished
by first registering the boundaries of the ROIs and then matching the
interiors of the ROIs using intensity registration.
The advantages of this approach include providing better registration
at the boundary of the ROI, eliminating registration errors caused by
registering regions outside the ROI, and theoretically
minimizing computation time since only the ROIs are registered.
The first step of the BICIR algorithm is to inverse consistently
register the boundaries of the ROIs. The resulting forward and reverse
boundary transformations are extended to the entire ROI domains
using the Element Free Galerkin Method (EFGM). The transformations
produced by the EFGM are then made inverse consistent by iteratively
minimizing the ICE. These transformations are used as initial conditions
for inverse-consistent intensity-based registration of the ROI interiors.
Weighted extended B-splines (WEB-splines) are used to parameterize the
transformations. WEB-splines are used instead of B-splines since
WEB-splines can be defined over an arbitrarily shaped ROI.
Results are presented showing that the BICIR method provides better
registration of 2D and 3D anatomical images than the small-deformation,
inverse-consistent, linear-elastic (SICLE) image registration algorithm which
registers entire images. Specifically, the BICIR method produced
registration results with lower similarity cost, reduced boundary
matching error, increased ROI relative overlap,
and lower inverse consistency error than the SICLE algorithm.
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Klepikova, Maria. "Imaging of fractured rock properties from flow and heat transport : field experiments and inverse modelling." Phd thesis, Université Rennes 1, 2013. http://tel.archives-ouvertes.fr/tel-00865302.
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La caracterisation de l'agencement spatial des proprietes hydrauliques est essentielle pour predire les ecoulements et le transport des solutes dans les milieux heterogenes. Les methodes de tomographie hydraulique, principalement developpees pour estimer les proprietes des milieux poreux, n'ont qu'une faible r'esolution spatiale qui ne reflete pas la vraie heterogeneite des distributions de fractures des milieux fractures. Le principal objectif de cette these est de developper une nouvelle methode d'inversion specifique pour imager les proprietés hydrauliques et de transport des milieux fractures a l'echelle du site. Pour atteindre ces objectifs, des experiences in situ ainsi qu'une nouvelle approche de modelisation inverse sont proposees, notamment en utilisant la temperature comme marqueur des ecoulements. Nous proposons tout d'abord la tomographie d'ecoulement bas'ee sur des tests s'equentiels de debimetrie entre puits, comme une nouvelle approche pour caracteriser la connectivit'e des fractures ainsi que leur transmissivite. A partir de simulations numeriques reproduisant des cas d'etudes synth'etiques, nous montrons que l'approche par tomographie r'eduit significativement l'incertitude sur les parametres estimes, et fournit une caracterisation detaillee du reseau de fracture sans requerir a l'utilisation d'obturateurs hydrauliques. Nous montrons ensuite comment les mesures de temperature peuvent etre utilisees pour quantifier les ecoulements dans les milieux fractur'es. Le grand int'erˆet d'utiliser la temperature est d'obtenir facilement et de facon continue en puits des profils de temp'erature. En utilisant un mod'ele numerique d'ecoulement et de transfert de chaleur a l'echelle du puits, une methode d'inversion pour estimer les vitesses d'ecoulement dans le puits 'a partir des donnes de temperature est proposee. Nous couplons ensuite les deux approches presentees precedemment dans une nouvelle approche experimentale consistant en des enregistrements sequentiels de temperature dans un puits dans des conditions de pompage entre puits. L'application de cette approche de tomographie en temperature sur le site de Stanger Brune montre des resultats encourageants pour l'identification du reseau global de connectivite et des zones d'ecoulement principales. Enfin, nous discutons de l'interet d'utiliser la chaleur comme traceur par rapport 'a l'utilisation de traceurs classiques. Nous montrons que realiser des tests de tracage thermiques en milieu fracture fournit des contraintes supplementaires importantes sur les propri'et'es de transport du milieu.
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Wonus, Julie L. (Julie Lynn). "A circuit model for diffusive breast imaging and a numerical algorithm for its inverse problem." Thesis, Massachusetts Institute of Technology, 1996. http://hdl.handle.net/1721.1/38172.
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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1996.Includes bibliographical references (leaves 67-70).
by Julie L. Wonus.
M.Eng.
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Alberti, Giovanni S. "On local constraints and regularity of PDE in electromagnetics : applications to hybrid imaging inverse problems." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:1b30b3b7-29b1-410d-ae30-bd0a87c9720b.
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The first contribution of this thesis is a new regularity theorem for time harmonic Maxwell's equations with less than Lipschitz complex anisotropic coefficients. By using the Lp theory for elliptic equations, it is possible to prove H1 and Hölder regularity results, provided that the coefficients are W1,p for some p = 3. This improves previous regularity results, where the assumption W1,∞ for the coefficients was believed to be optimal. The method can be easily extended to the case of bi-anisotropic materials, for which a separate approach turns out to be unnecessary. The second focus of this work is the boundary control of the Helmholtz and Maxwell equations to enforce local constraints inside the domain. More precisely, we look for suitable boundary conditions such that the corresponding solutions and their derivatives satisfy certain local non-zero constraints. Complex geometric optics solutions can be used to construct such illuminations, but are impractical for several reasons. We propose a constructive approach to this problem based on the use of multiple frequencies. The suitable boundary conditions are explicitly constructed and give the desired constraints, provided that a finite number of frequencies, given a priori, are chosen in a fixed range. This method is based on the holomorphicity of the solutions with respect to the frequency and on the regularity theory for the PDE under consideration. This theory finds applications to several hybrid imaging inverse problems, where the unknown coefficients have to be imaged from internal measurements. In order to perform the reconstruction, we often need to find suitable boundary conditions such that the corresponding solutions satisfy certain non-zero constraints, depending on the particular problem under consideration. The multiple frequency approach introduced in this thesis represents a valid alternative to the use of complex geometric optics solutions to construct such boundary conditions. Several examples are discussed.
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Barrera, Cruz Marco Antonio. "Hybrid method algebraic/inverse radon transform for region of interest reconstruction of computed tomography images /." To access this resource online via ProQuest Dissertations and Theses @ UTEP, 2009. http://0-proquest.umi.com.lib.utep.edu/login?COPT=REJTPTU0YmImSU5UPTAmVkVSPTI=&clientId=2515.
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Singh, Satyan. "An inverse scattering approach to imaging using Marchenko equations in the presence of a free surface." Thesis, Colorado School of Mines, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=10125227.
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The Green's function is the impulse response of a system and is used to infer the properties of the system from surface measurements. In exploration seismology, imaging algorithms use estimates of the Green's functions along with surface measurements to image the subsurface, i.e. locate the Earth's interfaces and its properties, so as to identify valuable energy resources. These conventional imaging algorithms only account for singly reflected waves (primaries) in the subsurface and hence, in the subsurface image, produce false interfaces in the presence of multiply reflected waves (internal and free-surface multiples).
Recent work has shown that we can retrieve the Green's function that accounts for primaries and internal multiples. Imaging with these Green's functions reduces the artifacts caused by internal multiples compared to conventional imaging algorithms. These Green's functions require the free-surface multiples to be removed from the surface measurements before retrieval and imaging.
I modify the retrieval of the Green's function to account for free-surface reflections and therefore no longer require the free-surface multiples to be removed from the surface measurements. Thus the Green's function, in the method I propose, includes not only primaries and internal multiples but also free-surface multiples. These Green's functions are constructed from an arbitrary point in the subsurface (no physical receiver is required at this location) to the surface.
The method I use to retrieve the Green's function does not specify the approach to image the subsurface. In this thesis I also analyze different imaging strategies using the retrieved Green's functions. Imaging with these Green's functions reduces the artifacts caused by multiply reflected waves compared to standard imaging algorithms. Significantly, the Green's function that I retrieve and use for imaging require the same inputs as conventional imaging algorithms: the surface measurements and a smooth version of the subsurface velocity.
I also extend the construction of the Green's function from the subsurface to the surface to any two arbitrary points in the subsurface (no physical source or physical receiver is required at either of these locations). This Green's function is called the virtual Green's function and includes all the primaries, internal and free-surface multiples. The virtual Green's function retrieval requires the same inputs as the previously mentioned Green's functions.
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Kim, Yong Yook. "Inverse Problems In Structural Damage Identification, Structural Optimization, And Optical Medical Imaging Using Artificial Neural Networks." Diss., Virginia Tech, 2004. http://hdl.handle.net/10919/11111.
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The objective of this work was to employ artificial neural networks (NN) to solve inverse problems in different engineering fields, overcoming various obstacles in applying NN to different problems and benefiting from the experience of solving different types of inverse problems. The inverse problems investigated are: 1) damage detection in structures, 2) detection of an anomaly in a light-diffusive medium, such as human tissue using optical imaging, 3) structural optimization of fiber optic sensor design. All of these problems require solving highly complex inverse problems and the treatments benefit from employing neural networks which have strength in generalization, pattern recognition, and fault tolerance. Moreover, the neural networks for the three problems are similar, and a method found suitable for solving one type of problem can be applied for solving other types of problems.
Solution of inverse problems using neural networks consists of two parts. The first is repeatedly solving the direct problem, obtaining the response of a system for known parameters and constructing the set of the solutions to be used as training sets for NN. The next step is training neural networks so that the trained neural networks can produce a set of parameters of interest for the response of the system. Mainly feed-forward backpropagation NN were used in this work.
One of the obstacles in applying artificial neural networks is the need for solving the direct problem repeatedly and generating a large enough number of training sets. To reduce the time required in solving the direct problems of structural dynamics and photon transport in opaque tissue, the finite element method was used. To solve transient problems, which include some of the problems addressed here, and are computationally intensive, the modal superposition and the modal acceleration methods were employed. The need for generating a large enough number of training sets required by NN was fulfilled by automatically generating the training sets using a script program in the MATLAB environment. This program automatically generated finite element models with different parameters, and the program also included scripts that combined the whole solution processes in different engineering packages for the direct problem and the inverse problem using neural networks.
Another obstacle in applying artificial neural networks in solving inverse problems is that the dimension and the size of the training sets required for the NN can be too large to use NN effectively with the available computational resources. To overcome this obstacle, Principal Component Analysis is used to reduce the dimension of the inputs for the NN without excessively impairing the integrity of the data. Orthogonal Arrays were also used to select a smaller number of training sets that can efficiently represent the given system.Ph. D.