Relevant bibliographies by topics / Assessment of image

Academic literature on the topic 'Assessment of image'

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Published: 14 March 2023

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Journal articles on the topic "Assessment of image"

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Golub, Y. I. "Image quality assessment." «System analysis and applied information science», no. 4 (January 5, 2022): 4–15. http://dx.doi.org/10.21122/2309-4923-2021-4-4-15.

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Quality assessment is an integral stage in the processing and analysis of digital images in various automated systems. With the increase in the number and variety of devices that allow receiving data in various digital formats, as well as the expansion of human activities in which information technology (IT) is used, the need to assess the quality of the data obtained is growing. As well as the bar grows for the requirements for their quality.The article describes the factors that deteriorate the quality of digital images, areas of application of image quality assessment functions, a method for normalizing proximity measures, classes of digital images and their possible distortions, image databases available on the Internet for conducting experiments on assessing image quality with visual assessments of experts.
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Han, Z., X. Tang, X. Gao, and F. Hu. "IMAGE FUSION AND IMAGE QUALITY ASSESSMENT OF FUSED IMAGES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-7/W1 (July 12, 2013): 33–36. http://dx.doi.org/10.5194/isprsarchives-xl-7-w1-33-2013.

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Starovoitov, V. V., Y. I. Golub, and M. M. Lukashevich. "Digital fundus image quality assessment." «System analysis and applied information science», no. 4 (January 5, 2022): 25–38. http://dx.doi.org/10.21122/2309-4923-2021-4-25-38.

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Diabetic retinopathy (DR) is a disease caused by complications of diabetes. It starts asymptomatically and can end in blindness. To detect it, doctors use special fundus cameras that allow them to register images of the retina in the visible range of the spectrum. On these images one can see features, which determine the presence of DR and its grade. Researchers around the world are developing systems for the automated analysis of fundus images. At present, the level of accuracy of classification of diseases caused by DR by systems based on machine learning is comparable to the level of qualified medical doctors.The article shows variants for representation of the retina in digital images by different cameras. We define the task to develop a universal approach for the image quality assessment of a retinal image obtained by an arbitrary fundus camera. It is solved in the first block of any automated retinal image analysis system. The quality assessment procedure is carried out in several stages. At the first stage, it is necessary to perform binarization of the original image and build a retinal mask. Such a mask is individual for each image, even among the images recorded by one camera. For this, a new universal retinal image binarization algorithm is proposed. By analyzing result of the binarization, it is possible to identify and remove imagesoutliers, which show not the retina, but other objects. Further, the problem of no-reference image quality assessment is solved and images are classified into two classes: satisfactory and unsatisfactory for analysis. Contrast, sharpness and possibility of segmentation of the vascular system on the retinal image are evaluated step by step. It is shown that the problem of no-reference image quality assessment of an arbitrary fundus image can be solved.Experiments were performed on a variety of images from the available retinal image databases.
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Golub, Yu I., F. V. Starovoitov, and V. V. Starovoitov. "Impact of image size reducing for image quality assesment." «System analysis and applied information science», no. 2 (August 18, 2020): 35–45. http://dx.doi.org/10.21122/2309-4923-2020-2-35-45.

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The article describes studies of the effect of image reduction on the quantitative assessment of their quality. Image reduction refers to the proportional reduction of horizontal and vertical image resolutions in pixels. Within the framework of these studies, correlation analysis between quantitative assessments of image quality and subjective assessments of experts was performed. For the experiments, we used images from the public TID2013 database with a resolution of 512 × 384 pixels and expert estimates of their quality, as well as photographs taken with a Nikon D5000 digital camera with a resolution of 4288 × 2848 pixels. All images were reduced in 2, 4 and 8 times. For this two methods were used: bilinear interpolation and interpolation by the nearest neighbor.22 measures were selected to evaluate image quality. Quantitative assessment of image quality was calculated in two stages. At the first stage, an array of local estimates was obtained in the vicinity of each pixel using the selected measures. At the second stage, a global quality assessment was calculated from the obtained local ones. To summarize local quality estimates, the parameters of 16 distributions of random variables were considered.According to the results of the experiments, it was concluded that the accuracy of the quality assessment for some measures decreases with image reduction (for example, FISH, GORD, HELM, LOEN measures). BREN and SHAR measures are recommended as the best. To reduce images, it is better to use the nearest neighbor interpolation method. At the same time, the computation time of estimates is reduced on average by 4 times while reducing images by 2 times. When images are reduced by 8 times, the calculation time decreases on average by 80 times. The amount of memory required to store the reduced images is 25 times less.
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Li, Zhipeng, Li Shen, and Linmei Wu. "IMAGE QUATY ASSESSMENT FOR VHR REMOTE SENSING IMAGE CLASSIFICATION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (June 17, 2016): 11–16. http://dx.doi.org/10.5194/isprs-archives-xli-b7-11-2016.

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The data from remote sensing images are widely used for characterizing land use and land cover at present. With the increasing availability of very high resolution (VHR) remote sensing images, the remote sensing image classification becomes more and more important for information extraction. The VHR remote sensing images are rich in details, but high within-class variance as well as low between-class variance make the classification of ground cover a difficult task. What’s more, some related studies show that the quality of VHR remote sensing images also has a great influence on the ability of the automatic image classification. Therefore, the research that how to select the appropriate VHR remote sensing images to meet the application of classification is of great significance. In this context, the factors of VHR remote sensing image classification ability are discussed and some indices are selected for describing the image quality and the image classification ability objectively. Then, we explore the relationship of the indices of image quality and image classification ability under a specific classification framework. The results of the experiments show that these image quality indices are not effective for indicating the image classification ability directly. However, according to the image quality metrics, we can still propose some suggestion for the application of classification.
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Li, Zhipeng, Li Shen, and Linmei Wu. "IMAGE QUATY ASSESSMENT FOR VHR REMOTE SENSING IMAGE CLASSIFICATION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (June 17, 2016): 11–16. http://dx.doi.org/10.5194/isprsarchives-xli-b7-11-2016.

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The data from remote sensing images are widely used for characterizing land use and land cover at present. With the increasing availability of very high resolution (VHR) remote sensing images, the remote sensing image classification becomes more and more important for information extraction. The VHR remote sensing images are rich in details, but high within-class variance as well as low between-class variance make the classification of ground cover a difficult task. What’s more, some related studies show that the quality of VHR remote sensing images also has a great influence on the ability of the automatic image classification. Therefore, the research that how to select the appropriate VHR remote sensing images to meet the application of classification is of great significance. In this context, the factors of VHR remote sensing image classification ability are discussed and some indices are selected for describing the image quality and the image classification ability objectively. Then, we explore the relationship of the indices of image quality and image classification ability under a specific classification framework. The results of the experiments show that these image quality indices are not effective for indicating the image classification ability directly. However, according to the image quality metrics, we can still propose some suggestion for the application of classification.
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Swarnkar, Santosh Kumar, and Prof Avinash Sharma. "Content-Based Image Retrieval: An Assessment." International Journal of Trend in Scientific Research and Development Volume-3, Issue-3 (April 30, 2019): 154–56. http://dx.doi.org/10.31142/ijtsrd21708.

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Boushey, C. J., M. Spoden, F. M. Zhu, E. J. Delp, and D. A. Kerr. "New mobile methods for dietary assessment: review of image-assisted and image-based dietary assessment methods." Proceedings of the Nutrition Society 76, no. 3 (December 12, 2016): 283–94. http://dx.doi.org/10.1017/s0029665116002913.

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For nutrition practitioners and researchers, assessing dietary intake of children and adults with a high level of accuracy continues to be a challenge. Developments in mobile technologies have created a role for images in the assessment of dietary intake. The objective of this review was to examine peer-reviewed published papers covering development, evaluation and/or validation of image-assisted or image-based dietary assessment methods from December 2013 to January 2016. Images taken with handheld devices or wearable cameras have been used to assist traditional dietary assessment methods for portion size estimations made by dietitians (image-assisted methods). Image-assisted approaches can supplement either dietary records or 24-h dietary recalls. In recent years, image-based approaches integrating application technology for mobile devices have been developed (image-based methods). Image-based approaches aim at capturing all eating occasions by images as the primary record of dietary intake, and therefore follow the methodology of food records. The present paper reviews several image-assisted and image-based methods, their benefits and challenges; followed by details on an image-based mobile food record. Mobile technology offers a wide range of feasible options for dietary assessment, which are easier to incorporate into daily routines. The presented studies illustrate that image-assisted methods can improve the accuracy of conventional dietary assessment methods by adding eating occasion detail via pictures captured by an individual (dynamic images). All of the studies reduced underreporting with the help of images compared with results with traditional assessment methods. Studies with larger sample sizes are needed to better delineate attributes with regards to age of user, degree of error and cost.
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Fernandez-Maloigne, Christine, Jaime Moreno, Alessandro Rizzi, and Cristian Bonanomi. "QUALITAS: Image Quality Assessment for Stereoscopic Images." Color and Imaging Conference 2016, no. 1 (November 7, 2016): 7–19. http://dx.doi.org/10.2352/issn.2169-2629.2017.32.7.

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Fernandez-Maloigne, Christine, Jaime Moreno, Alessandro Rizzi, and Cristian Bonanomi. "QUALITAS: Image Quality Assessment for Stereoscopic Images." Journal of Imaging Science and Technology 60, no. 5 (September 1, 2016): 504051–5040513. http://dx.doi.org/10.2352/j.imagingsci.technol.2016.60.5.050405.

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Dissertations / Theses on the topic "Assessment of image"

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Verhaaren, Catharine C. "Improving Course Assessments Through a Product Assessment Template." Diss., CLICK HERE for online access, 2008. http://contentdm.lib.byu.edu/ETD/image/etd2338.pdf.

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Šmida, Vladimír. "Fingerprint Image Quality Assessment." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2011. http://www.nusl.cz/ntk/nusl-237090.

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Kritickým prvkem biometrického systému pro rozpoznávání otisků prstů je proces snímání. Kvalita snímku totiž ovlivňuje všechny další části systému počínaje zpracováním obrazu, přes extrakci rysů až po samotné rozhodnutí. Přestože bylo navrženo několik metod určování kvality snímku, chybějící formální specifikace kvality otisku nedovoluje ověřit jejich přesnost. Tato diplomová práce se zabývá hodnocením metod určujících kvalitu biometrického signálu otisku prstu. Popisuje jednotlivé faktory ovlivňující kvalitu spolu se současnými přístupy používanými pro její odhad. V práci je rovněž vysvětlena evaluační technika navržená za účelem porovnání schopnosti jednotlivých metod předpovědět výkon biometrického systému. Několik metod pro odhad kvality bylo implementováno a ohodnoceno touto technikou.
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Cheng, Wu. "Corrupted Image Quality Assessment." University of Dayton / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1335969249.

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Cui, Lei. "Topics in image recovery and image quality assessment /Cui Lei." HKBU Institutional Repository, 2016. https://repository.hkbu.edu.hk/etd_oa/368.

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Image recovery, especially image denoising and deblurring is widely studied during the last decades. Variational models can well preserve edges of images while restoring images from noise and blur. Some variational models are non-convex. For the moment, the methods for non-convex optimization are limited. This thesis finds new non-convex optimizing method called difference of convex algorithm (DCA) for solving different variational models for various kinds of noise removal problems. For imaging system, noise appeared in images can show different kinds of distribution due to the different imaging environment and imaging technique. Here we show how to apply DCA to Rician noise removal and Cauchy noise removal. The performance of our experiments demonstrates that our proposed non-convex algorithms outperform the existed ones by better PSNR and less computation time. The progress made by our new method can improve the precision of diagnostic technique by reducing Rician noise more efficiently and can improve the synthetic aperture radar imaging precision by reducing Cauchy noise within. When applying variational models to image denoising and deblurring, a significant subject is to choose the regularization parameters. Few methods have been proposed for regularization parameter selection for the moment. The numerical algorithms of existed methods for parameter selection are either complicated or implicit. In order to find a more efficient and easier way to estimate regularization parameters, we create a new image quality sharpness metric called SQ-Index which is based on the theory of Global Phase Coherence. The new metric can be used for estimating parameters for a various of variational models, but also can estimate the noise intensity based on special models. In our experiments, we show the noise estimation performance with this new metric. Moreover, extensive experiments are made for dealing with image denoising and deblurring under different kinds of noise and blur. The numerical results show the robust performance of image restoration by applying our metric to parameter selection for different variational models.
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Zhang, Wei. "Visual saliency in image quality assessment." Thesis, Cardiff University, 2017. http://orca.cf.ac.uk/100239/.

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Advances in image quality assessment have shown the benefits of modelling functional components of the human visual system in image quality metrics. Visual saliency, a crucial aspect of the human visual system, is increasingly investigated recently. Current applications of visual saliency in image quality metrics are limited by our knowledge on the relation between visual saliency and quality perception. Issues regarding how to simulate and integrate visual saliency in image quality metrics remain. This thesis presents psychophysical experiments and computational models relevant to the perceptually-optimised use of visual saliency in image quality metrics. We first systematically validated the capability of computational saliency in improving image quality metrics. Practical guidance regarding how to select suitable saliency models, which image quality metrics can benefit from saliency integration, and how the added value of saliency depends on image distortion type were provided. To better understand the relation between saliency and image quality, an eye-tracking experiment with a reliable experimental methodology was first designed to obtain ground truth fixation data. Significant findings on the interactions between saliency and visual distortion were then discussed. Based on these findings, a saliency integration approach taking into account the impact of distortion on the saliency deployment was proposed. We also devised an algorithm which adaptively incorporate saliency in image quality metrics based on saliency dispersion. Moreover, we further investigated the plausibility of measuring image quality based on the deviation of saliency induced by distortion. An image quality metric based on measuring saliency deviation was devised. This thesis demonstrates that the added value of saliency in image quality metrics can be optimised by taking into account the interactions between saliency and visual distortion. This thesis also demonstrates that the deviation of fixation deployment due to distortion can be used as a proxy for the prediction of image quality.
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Ivkovic, Goran. "An Algorithm for Image Quality Assessment." [Tampa, Fla.] : University of South Florida, 2003. http://purl.fcla.edu/fcla/etd/SFE0000049.

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CORCHS, SILVIA ELENA. "Image quality assessment for Digital documents." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2014. http://hdl.handle.net/10281/50461.

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This thesis focuses on No Reference (NR) methods for Image Quality Assessment (IQA). A review of the IQA field is presented in Chapter 2; where the different IQA methods are described and classified. In particular, the application of IQA methods within a workflow chain is discussed. In Chapter 3 we focus on NR metrics for JPEG-blockiness and noise artifacts. It is in general assumed that subjective methods produce an actual estimate of the perceived quality while objective methods produce values that should be correlated with human perceptions as best as possible. From the analysis of the regression curves that correlate objective and subjective data we have found that in some cases the metric's predictions are not in correspondence with the subjective scores. After reviewing the available databases, we realize that the distortion ranges considered are not in general representative of real case applications. Therefore, in Chapter 4 the Imaging and Vision Lab (IVL) database is introduced. It was generated with the aim of assessing the quality of images corrupted by JPEG and noise. In Chapter 5 we approach the NR-IQA field by focusing on a classification problem. A framework based on machine learning classification is proposed that let us evaluate how images can be classified within different groups or classes, according to their quality. NR metrics are considered as features and the assigned classes are obtained from the psychovisual data. For the JPEG distortion case, the feature space of the classifiers is built using each NR metric as single feature and also a pool of eleven NR metrics. Classification within five and three classes was addressed. In the former case, the five classes are in correspondence to the five categories recommended by the ITU (excellent, good, fair, poor, and bad) when designing image quality experiments. In the latter case we were interested in classifying images as high, medium or low quality ones. The classifiers are trained and tested on different databases. The classifier obtained using the pool of metrics outperforms each single metric classifier. Better performance is obtained in the case of three classes. Considering an image as the combining of two signals, content and distortion, we note that the crosstalk between both signals influences both subjective and objective quality assessment. We address this problem in Chapter 6 where our working hypothesis is that regression can be improved if performed within a group of images that present similar contents in terms of low level features. The criteria chosen to divide the images in different groups is the image complexity. The proposed strategy consists on two steps: the images (of a given database) are first classified in three groups of low, medium and high complexity. In a second step, regression is performed within each of these groups separately. The strategy is tested for different NR metrics for JPEG-blockiness and noise artifacts, different databases are considered. Correlation coefficients are computed and statistical significance tests are applied. The gain in performance depends on the metric and distortion considered. Summarizing, the two main proposals of this research work, i.e. the classification approach that combines several NR metrics and the grouping strategy, are able to outperform the correlation between subjective and objective data for the case of JPEG-blockiness. Both strategies can be extended to consider other type of distortions.
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Rousselot, Maxime. "Image quality assessment of High Dynamic Range and Wide Color Gamut images." Thesis, Rennes 1, 2019. http://www.theses.fr/2019REN1S034/document.

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Ces dernières années, les technologies d’écran se sont considérablement améliorées. Par exemple, le contraste des écrans à plage dynamique élevée (HDR) dépasse de loin la capacité d’un écran conventionnel. De plus, un écran à gamut de couleur étendu (WCG) peut couvrir un espace colorimétrique plus grand que jamais. L'évaluation de la qualité de ces nouveaux contenus est devenue un domaine de recherche actif, les métriques de qualité SDR classiques n'étant pas adaptées. Cependant, les études les plus récentes négligent souvent une caractéristique importante: les chrominances. En effet, les bases de données existantes contiennent des images HDR avec un gamut de couleur standard, négligeant ainsi l’augmentation de l’espace colorimétrique due au WCG et les artefacts chromatiques. La plupart des mesures de qualité HDR objectives non plus ne prennent pas en compte ces artefacts. Pour surmonter cette problématique, dans cette thèse, nous proposons deux nouvelles bases de données HDR/WCG annotés avec des scores subjectifs présentant des artefacts chromatique réaliste. En utilisant ces bases de données, nous explorons trois solutions pour créer des métriques HDR/WCG: l'adaptation des métrics de qualité SDR, l’extension colorimétrique d’une métrique HDR connue appelée HDR-VDP-2 et, enfin, la fusion de diverses métriques de qualité et de features colorimétriques. Cette dernière métrique présente de très bonnes performances pour prédire la qualité tout en étant sensible aux distorsions chromatiques
To improve their ability to display astonishing images, screen technologies have been greatly evolving. For example, the contrast of high dynamic range rendering systems far exceed the capacity of a conventional display. Moreover, a Wide Color gamut display can cover a bigger color space than ever. Assessing the quality of these new content has become an active field of research as classical SDR quality metrics are not adapted. However, state-of-the-art studies often neglect one important image characteristics: chrominances. Indeed, previous databases contain HDR images with a standard gamut thus neglecting the increase of color space due to WCG. Due to their gamut, these databases are less prone to contain chromatic artifacts than WCG content. Moreover, most existing HDR objective quality metrics only consider luminance and are not considering chromatic artifacts. To overcome this problematic, in this thesis, we have created two HDR / WCG databases with annotated subjective scores. We focus on the creation of a realistic chromatic artifacts that can arise during compression. In addition, using these databases, we explore three solutions to create HDR / WCG metrics. First, we propose a method to adapt SDR metrics to HDR / WCG content. Then, we proposed an extension of a well-known HDR metric called HDR-VDP-2. Finally, we create a new metric based on the merger of various quality metric and color features. This last metric presents very good performance to predict quality while being sensitive to chromatic distortion
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Bjurström, Håkan, and Jon Svensson. "Assessment of Grapevine Vigour Using Image Processing." Thesis, Linköping University, Department of Electrical Engineering, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-1342.

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This Master’s thesis studies the possibility of using image processing as a tool to facilitate vine management, in particular shoot counting and assessment of the grapevine canopy. Both are areas where manual inspection is done today. The thesis presents methods of capturing images and segmenting different parts of a vine. It also presents and evaluates different approaches on how shoot counting can be done. Within canopy assessment, the emphasis is on methods to estimate canopy density. Other possible assessment areas are also discussed, such as canopy colour and measurement of canopy gaps and fruit exposure. An example of a vine assessment system is given.

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Sendashonga, Mireille. "Image quality assessment using frequency domain transforms." Thesis, McGill University, 2006. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=99537.

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Measurement of image quality plays a central role in optimization and evaluation of imaging systems. The most straight-forward way to assess image quality is subjective evaluations by human observers, where the mean value of their scores is used as the quality measure. However, objective (quantitative) measures are needed because subjective evaluations are impractical and expensive. The aim of this thesis is to develop simple and low-complexity metrics for quality assessment of digital images.
Traditionally, the most widely used quantitative measures are the mean squared error and measures that model the human visual system. The proposed method uses the Discrete Cosine Transform and the Discrete Wavelet Transform to divide images into four frequency bands and relates the visual quality of the distorted images to the weighted average of the mean squared error between original and distorted images within each band.
The performance of the metrics presented in this thesis is tested and validated on a large database of subjective quality ratings. Simulations show that the proposed metrics accurately predict visual quality and outperform current state-of-the-art methods with simple and easily implemented processing steps.
Extensions of the proposed image quality metrics are investigated. More particularly, this thesis explores image quality assessment when the reference image is only partially available (reduced reference settings), and presents a method for successfully quantifying the quality of distorted images in such settings.
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Books on the topic "Assessment of image"

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Bigand, André, Julien Dehos, Christophe Renaud, and Joseph Constantin. Image Quality Assessment of Computer-generated Images. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73543-6.

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Wang, Zhou, and Alan C. Bovik. Modern Image Quality Assessment. Cham: Springer International Publishing, 2006. http://dx.doi.org/10.1007/978-3-031-02238-8.

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Ding, Yong, and Guangming Sun. Stereoscopic Image Quality Assessment. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-7764-2.

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Tarkowski, Zbigniew. Assessment and self-assessment of stuttering and self-image. Olsztyn: University of Marmia and Mazury, 2010.

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Body image disturbance: Assessment and treatment. Elmsford, N.Y., U.S.A: Pergamon Press, 1990.

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Szapiel, Stanisław. Diffraction-based image assessment in optical design. Warszawa: Wydawn. Politechniki Warszawskiej, 1986.

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Ding, Yong. Visual Quality Assessment for Natural and Medical Image. Berlin, Heidelberg: Springer Berlin Heidelberg, 2018. http://dx.doi.org/10.1007/978-3-662-56497-4.

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Centre national d'études spatiales (France)., ed. Spot 1, utilisation des images, bilan, résultats =: Spot 1, image utilization, assessment, results. Toulouse, France: CEPADUES-Editions, 1988.

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Zhu, Shu-Yu. Perceptual wavelet coding and quality assessment for still image. Ottawa: National Library of Canada, 2000.

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The inner image: A resource for type development. Palo Alto, CA: Consulting Psychologists Press, 1990.

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Book chapters on the topic "Assessment of image"

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Zamzmi, Ghada, Chih-Yun Pai, Dmitry Goldgof, Rangachar Kasturi, Yu Sun, and Terri Ashmeade. "Automated Pain Assessment in Neonates." In Image Analysis, 350–61. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-59129-2_30.

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Ortiz-Jaramillo, B., L. Platisa, and W. Philips. "iFAS: Image Fidelity Assessment." In Lecture Notes in Computer Science, 83–94. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56010-6_7.

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Ding, Yong. "Stereoscopic Image Quality Assessment." In Visual Quality Assessment for Natural and Medical Image, 161–213. Berlin, Heidelberg: Springer Berlin Heidelberg, 2018. http://dx.doi.org/10.1007/978-3-662-56497-4_7.

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Ding, Yong. "Medical Image Quality Assessment." In Visual Quality Assessment for Natural and Medical Image, 215–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 2018. http://dx.doi.org/10.1007/978-3-662-56497-4_8.

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Andrade, Juan. "No-Reference Image Assessment." In A Survey of Blur Detection and Sharpness Assessment Methods, 57–72. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-031-01529-8_4.

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Langs, Georg, Philipp Peloschek, and Horst Bischof. "ASM Driven Snakes in Rheumatoid Arthritis Assessment." In Image Analysis, 454–61. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-45103-x_61.

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Jannin, Pierre, and Werner Korb. "Assessment of Image-Guided Interventions." In Image-Guided Interventions, 531–49. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-73858-1_18.

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Chaudhuri, Subhasis, and Ketan Kotwal. "Performance Assessment of Fusion Techniques." In Hyperspectral Image Fusion, 127–49. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-7470-8_9.

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Tipker-Vos, Corinne, Kim de Crom, Anouk van der Gijp, Cécile Ravesloot, M. van der Schaaf, Christian Mol, Mario Maas, Jan van Schaik, and Koen Vincken. "Practical Implementation of Innovative Image Testing." In Computer Assisted Assessment. Research into E-Assessment, 145–48. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08657-6_14.

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Wang, Zhou, and Alan C. Bovik. "No-Reference Image Quality Assessment." In Modern Image Quality Assessment, 79–102. Cham: Springer International Publishing, 2006. http://dx.doi.org/10.1007/978-3-031-02238-8_4.

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Conference papers on the topic "Assessment of image"

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Mitra, Sunanda, Vinod Chandran, Thomas F. Krile, and Dah-Jye Lee. "Fundus Image Registration Algorithms for a PC-Based Image Processing System." In Noninvasive Assessment of the Visual System. Washington, D.C.: Optica Publishing Group, 1987. http://dx.doi.org/10.1364/navs.1987.md4.

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Fundus photographs are routinely taken in an ophthalmology clinic to monitor feature changes in the suspected regions of the retina. For quantitative evaluation of subtle changes in the fundus from the photographs taken over a period of time using digital image processing, the fundus images have to be registered to a reference image, usually, the image of the same fundus taken earlier. The problem of registering one digital image with another reduces to that of finding local similarity between two structural data sets.
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Whiteside, Steven, Alice Ling, Sunanda Mitra, Thomas F. Krile, and Zuhair Shihab. "Image Enhancement of Nerve Fiber Layers in Glaucoma." In Noninvasive Assessment of the Visual System. Washington, D.C.: Optica Publishing Group, 1986. http://dx.doi.org/10.1364/navs.1986.wb4.

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Digital image enhancement and restoration techniques have been used in noninvasive diagnostic radiographic imaging for quite some time.1 Application of digital image processing to enhance fundus photographs is relatively recent. Basic problems in standardization, restoration of fundus images and development of an optimal image enhancement procedure for specific applications are being presently investigated by researchers.2,3,6 Enhancement of fundus photographs is of particular significance in diseases such as glaucoma where structural changes in the optic nerve head and retinal nerve fiber layers are indicative of the progression of the disease.4,5 We have examined the fundus photographs of a group of normal and glaucoma patients where structural changes in nerve fiber layers in specific zones of the fundus were highlighted when a combination of restoration and enhancement procedures were employed.6
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Rajagopal, Heshalini, Norrima Mokhtar, and Anis Salwa Mohd Khairuddin. "Image Quality Assessment for Wood Images." In 2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET). IEEE, 2022. http://dx.doi.org/10.1109/iicaiet55139.2022.9936864.

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Madhusudana, Pavan C., Neil Birkbeck, Yilin Wang, Balu Adsumilli, and Alan C. Bovik. "Image Quality Assessment using Synthetic Images." In 2022 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW). IEEE, 2022. http://dx.doi.org/10.1109/wacvw54805.2022.00015.

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Jamson, Hamish. "Image Characteristics and Their Effect on Driving Simulator Validity." In Driving Assessment Conference. Iowa City, Iowa: University of Iowa, 2001. http://dx.doi.org/10.17077/drivingassessment.1036.

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Rouse, David M., Romuald Pepion, Sheila S. Hemami, and Patrick Le Callet. "Image utility assessment and a relationship with image quality assessment." In IS&T/SPIE Electronic Imaging, edited by Bernice E. Rogowitz and Thrasyvoulos N. Pappas. SPIE, 2009. http://dx.doi.org/10.1117/12.811664.

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Wang, Y., and D. Durmus. "Variability in image quality assessment metrics with different image capturing devices." In Optical Devices and Materials for Solar Energy and Solid-state Lighting. Washington, D.C.: Optica Publishing Group, 2022. http://dx.doi.org/10.1364/pvled.2022.pvm3h.5.

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Occupants’ subjective evaluations of the visual environment can be estimated using image quality assessment metrics. Images captured by a webcam, iPhone, and HDR camera resulted in only small differences in image quality metrics.
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Wang, Guolong, Junchi Yan, and Zheng Qin. "Collaborative and Attentive Learning for Personalized Image Aesthetic Assessment." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/133.

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The ever-increasing volume of visual images has stimulated the demand for organizing such data by aesthetic quality. Automatic and especially learning based aesthetic assessment methods have shown potential by recent works. Existing image aesthetic prediction is often user-agnostic which may ignore the fact that the rating to an image can be inherently individual. We fill this gap by formulating the personalized image aesthetic assessment problem with a novel learning method. Specifically, we collect user-image textual reviews in addition with visual images from the public dataset to organize a review-augmented benchmark. Using this enriched dataset, we devise a deep neural network with a user/image relation encoding input for collaborative filtering. Meanwhile an attentive mechanism is designed to capture the user-specific taste for image semantic tags and regions of interest by fusing the image and user's review. Extensive and promising experimental results on the review-augmented benchmark corroborate the efficacy of our approach.
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Uchida, Akira, Masaaki Fujiyoshi, Sayaka Shiota, and Hitoshi Kiya. "Image invisibility assessment for visually encrypted images." In 2014 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS). IEEE, 2014. http://dx.doi.org/10.1109/ispacs.2014.7024427.

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Behrens, Alexander, Michael Bommes, Sebastian Gross, and Til Aach. "Image quality assessment of endoscopic panorama images." In 2011 18th IEEE International Conference on Image Processing (ICIP 2011). IEEE, 2011. http://dx.doi.org/10.1109/icip.2011.6116325.

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Reports on the topic "Assessment of image"

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Schoening, T., and J. Greinert. Quality of image-based manganese nodule abundance assessment. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2017. http://dx.doi.org/10.4095/305928.

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Pelizzari, Charles A>. Image Guidance and Assessment of Radiation Induced Gene Therapy. Fort Belvoir, VA: Defense Technical Information Center, February 2004. http://dx.doi.org/10.21236/ada424653.

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Wales, Jesse G., and Peter L. Marasco. Assessment of an Optically Stimulated Infrared Emission From Image Intensifier Tube Photocathodes. Fort Belvoir, VA: Defense Technical Information Center, October 2005. http://dx.doi.org/10.21236/ada442754.

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Nelson, Cynthia Lee. Fusion of image data for beyond-the-fence intruder detection and assessment. Office of Scientific and Technical Information (OSTI), September 2007. http://dx.doi.org/10.2172/920447.

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Kane, Joshua James, and William Enoch Windes. Initial Assessment of X-Ray Computer Tomography image analysis for material defect microstructure. Office of Scientific and Technical Information (OSTI), June 2016. http://dx.doi.org/10.2172/1364233.

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Beauchemin, M., K. B. Fung, and X. Geng. A Method Based on Local Variance for Quality Assessment of Multiresolution Image Fusion. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2002. http://dx.doi.org/10.4095/219921.

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Guindon, B. Computer-based aerial image understanding: a review and assessment of its application to planimetric information extraction from very high resolution satellite images. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1997. http://dx.doi.org/10.4095/218537.

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Yen, M. S. C., P. T. C. Chu, and K. Ho. Development of an on-line image analysis for assessment of pyrite liberation. Technical report, December 1, 1992--February 28, 1993. Office of Scientific and Technical Information (OSTI), May 1993. http://dx.doi.org/10.2172/10151429.

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Yen, S. C. M., and P. T. C. Chu. Development of an on-line image analysis for assessment of pyrite liberation. Final technical report, 1 September, 1992--31 August, 1993. Office of Scientific and Technical Information (OSTI), December 1993. http://dx.doi.org/10.2172/10132232.

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Gantzer, Clark J., Shmuel Assouline, and Stephen H. Anderson. Synchrotron CMT-measured soil physical properties influenced by soil compaction. United States Department of Agriculture, February 2006. http://dx.doi.org/10.32747/2006.7587242.bard.

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Methods to quantify soil conditions of pore connectivity, tortuosity, and pore size as altered by compaction were done. Air-dry soil cores were scanned at the GeoSoilEnviroCARS sector at the Advanced Photon Source for x-ray computed microtomography of the Argonne facility. Data was collected on the APS bending magnet Sector 13. Soil sample cores 5- by 5-mm were studied. Skeletonization algorithms in the 3DMA-Rock software of Lindquist et al. were used to extract pore structure. We have numerically investigated the spatial distribution for 6 geometrical characteristics of the pore structure of repacked Hamra soil from three-dimensional synchrotron computed microtomography (CMT) computed tomographic images. We analyzed images representing cores volumes 58.3 mm³ having average porosities of 0.44, 0.35, and 0.33. Cores were packed with < 2mm and < 0.5mm sieved soil. The core samples were imaged at 9.61-mm resolution. Spatial distributions for pore path length and coordination number, pore throat size and nodal pore volume obtained. The spatial distributions were computed using a three-dimensional medial axis analysis of the void space in the image. We used a newly developed aggressive throat computation to find throat and pore partitioning for needed for higher porosity media such as soil. Results show that the coordination number distribution measured from the medial axis were reasonably fit by an exponential relation P(C)=10⁻C/C0. Data for the characteristic area, were also reasonably well fit by the relation P(A)=10⁻ᴬ/ᴬ0. Results indicates that compression preferentially affects the largest pores, reducing them in size. When compaction reduced porosity from 44% to 33%, the average pore volume reduced by 30%, and the average pore-throat area reduced by 26%. Compaction increased the shortest paths interface tortuosity by about 2%. Soil structure alterations induced by compaction using quantitative morphology show that the resolution is sufficient to discriminate soil cores. This study shows that analysis of CMT can provide information to assist in assessment of soil management to ameliorate soil compaction.
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