Dissertations / Theses on the topic 'Digital image restoration'
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Sandor, Viviana. "Wavelet-based digital image restoration." W&M ScholarWorks, 1998. https://scholarworks.wm.edu/etd/1539623937.
Full textHazra, Rajeeb. "Constrained least-squares digital image restoration." W&M ScholarWorks, 1995. https://scholarworks.wm.edu/etd/1539623865.
Full textAhtaiba, Ahmed Mohamed A. "Restoration of AFM images using digital signal and image processing." Thesis, Liverpool John Moores University, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.604322.
Full textKatsaggelos, Aggelos Konstantinos. "Constrained iterative image restoration algorithms." Diss., Georgia Institute of Technology, 1985. http://hdl.handle.net/1853/15830.
Full textYau, Chin-ko, and 游展高. "Super-resolution image restoration from multiple decimated, blurred and noisy images." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2004. http://hub.hku.hk/bib/B30292529.
Full textMORGAN, KEITH PATRICK. "IMPROVED METHODS OF IMAGE SMOOTHING AND RESTORATION (NONSTATIONARY MODELS)." Diss., The University of Arizona, 1985. http://hdl.handle.net/10150/187959.
Full textHamed, Mahmoud S. "Film and video restoration using nonlinear digital image processing techniques." Thesis, University of Strathclyde, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.400321.
Full textRevelant, Ivan L. "Restoration of images degraded by systems of random impulse response." Thesis, University of British Columbia, 1987. http://hdl.handle.net/2429/26731.
Full textApplied Science, Faculty of
Electrical and Computer Engineering, Department of
Graduate
BRUEGGE, THOMAS JOSEPH. "THE USE OF FINITE IMPULSE RESPONSE KERNELS FOR IMAGE RESTORATION." Diss., The University of Arizona, 1985. http://hdl.handle.net/10150/187974.
Full textBurger, R. E. "Investigations relating to the computer restoration of ultrasonic sector scan images." Thesis, University of Cambridge, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.233704.
Full text沈逸江 and Yijiang Shen. "Binary image restoration by positive semidefinite programming and signomial programming." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2007. http://hub.hku.hk/bib/B39557431.
Full textNamroud, Iman. "An Analysis of Aliasing and Image Restoration Performance for Digital Imaging Systems." University of Dayton / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1399046084.
Full textLie, Chin Cheong Patrick. "Iterative algorithms for fast, signal-to-noise ratio insensitive image restoration." Thesis, McGill University, 1987. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=63767.
Full textIgnácio, Ubiratã Azevedo. "Aplicação de wavelets em inpainting digital." Universidade do Vale do Rio do Sinos, 2007. http://www.repositorio.jesuita.org.br/handle/UNISINOS/2245.
Full textCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
Inpainting Digital é uma técnica recente que permite completar a falta de informação em imagens, seja por falha ou por remoção intencional de alguma área ou objeto. Uma das atribuições importantes do inpainting digital é de que deve ser capaz de alterar uma imagem, de forma que não seja simples perceber que esta alteração foi feita; caracteriza uma modificação indetectável. Os métodos para determinar como esta falta de informação será preenchida variam desde a criação do primeiro modelo de inpainting digital. Contudo, sempre deve ser mantida uma coerência no preenchimento, que fará com que a região preenchida automaticamente aparente como parte da imagem verdadeira. As técnicas atuais tratam este preenchimento como uma propagação da estrutura da área que está ao redor da região a ser preenchida, trabalhando diretamente no domímio das cores, utilizando abordagens como Variação Total e Equações Diferenciais Parciais. Neste trabalho, é feito o uso de transformada Wavelet para a aplicação de inpainting digita
Digital Inpainting is a recent techinique that allows the filling of missing information in images. One important attribute of a digital inpainting technique is the ability of altering an image in such a way that it is not simple for the human observer to detect the modification, characterizing an undetectable modification. The strategies for filling missing parts vary since the first inpainting model, but one thing that remains is the fact that the filled area must be coherent with the original part of the image. Current techniques handle the filling as a structure propagation problem, working directly in the image color domain, and based on concepts like Total Variation or Partial Diferential Equations. In this work, we present a digital inpainting model that works exclusively in Wavelet domain,filling the target area with a texture synthesis mechanism using the properties of the Wavelet Transform
Rucci, Michael. "Computationally Efficient Video Restoration for Nyquist Sampled Imaging Sensors Combining an Affine-Motion Based Temporal Kalman Filter and Adaptive Wiener Filter." University of Dayton / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1398286798.
Full textBuda, Bajić Papuga. "Methods for image restoration and segmentation by sparsity promoting energy minimization." Phd thesis, Univerzitet u Novom Sadu, Fakultet tehničkih nauka u Novom Sadu, 2019. https://www.cris.uns.ac.rs/record.jsf?recordId=110640&source=NDLTD&language=en.
Full textПоступак минимизације функције енергије је често коришћен зарешавање проблема у обради дигиталне слике. Предмет истраживањатезе су два круцијална задатка дигиталне обраде слике: рестаурација исегментација слика деградираних шумом и замагљењем. И рестaурацијаи сегментација су моделовани као проблеми минимизације функцијеенергије која представља збир две функције: функције фитовањаподатака и регуларизационе функције. Главни допринос тезе је развојнових функција фитовања података и нових регуларизационих функцијаза рестаурацију и сегментацију.Методе за рестаурацију (оне код којих је функција замагљења позната икод којих је функцију замагљења потребно оценити на основу датихподатака као и методе за реконструкцију слике у супер-резолуцији)развијене у оквиру ове тезе третирају мешавину Поасоновог и Гаусовогшума који се појављује у многобројним реалистичним сценаријима. Затретирање такве врсте шума користили смо нелинеарну трансформацијуи предложили смо нову функцију фитовања података која узима у обзиртакву трансформацију. У вези са регуларизационим функцијама смотестирали хипотезу да се функција Тоталне Варијације која промовишеретку слику у градијентном домену може побољшати уколико се користетзв. потенцијалне функције. Показали смо да се употребом Хуберовепотенцијалне функције може значајно побољшати квалитет рестауриранеслике која је деградирана замагљењем и мешавином Поасоновог иГаусовог шума.У оквиру тезе смо предложили нову методу сегментације која допуштаделимичну покривеност пиксела објектом. Функција фитовања податакаове методе укључује и модел замагљења и смањења резолуције. На тајначин је постигнута робустност сегментације у присуству замагљења идобијена могућност сегментирања слике у супер-резолуцији. Додатно,нове регуларизационе функције које промовишу ретке репрезентацијеслике су предложене.Предложене методе рестаурације и сегментације која допушта делимичнупокривеност пиксела објектом су примењене на слике добијене помоћуелектронског микроскопа, хиперспектралне слике и медицинске ЦТ слике.
Postupak minimizacije funkcije energije je često korišćen zarešavanje problema u obradi digitalne slike. Predmet istraživanjateze su dva krucijalna zadatka digitalne obrade slike: restauracija isegmentacija slika degradiranih šumom i zamagljenjem. I restauracijai segmentacija su modelovani kao problemi minimizacije funkcijeenergije koja predstavlja zbir dve funkcije: funkcije fitovanjapodataka i regularizacione funkcije. Glavni doprinos teze je razvojnovih funkcija fitovanja podataka i novih regularizacionih funkcijaza restauraciju i segmentaciju.Metode za restauraciju (one kod kojih je funkcija zamagljenja poznata ikod kojih je funkciju zamagljenja potrebno oceniti na osnovu datihpodataka kao i metode za rekonstrukciju slike u super-rezoluciji)razvijene u okviru ove teze tretiraju mešavinu Poasonovog i Gausovogšuma koji se pojavljuje u mnogobrojnim realističnim scenarijima. Zatretiranje takve vrste šuma koristili smo nelinearnu transformacijui predložili smo novu funkciju fitovanja podataka koja uzima u obzirtakvu transformaciju. U vezi sa regularizacionim funkcijama smotestirali hipotezu da se funkcija Totalne Varijacije koja promovišeretku sliku u gradijentnom domenu može poboljšati ukoliko se koristetzv. potencijalne funkcije. Pokazali smo da se upotrebom Huberovepotencijalne funkcije može značajno poboljšati kvalitet restauriraneslike koja je degradirana zamagljenjem i mešavinom Poasonovog iGausovog šuma.U okviru teze smo predložili novu metodu segmentacije koja dopuštadelimičnu pokrivenost piksela objektom. Funkcija fitovanja podatakaove metode uključuje i model zamagljenja i smanjenja rezolucije. Na tajnačin je postignuta robustnost segmentacije u prisustvu zamagljenja idobijena mogućnost segmentiranja slike u super-rezoluciji. Dodatno,nove regularizacione funkcije koje promovišu retke reprezentacijeslike su predložene.Predložene metode restauracije i segmentacije koja dopušta delimičnupokrivenost piksela objektom su primenjene na slike dobijene pomoćuelektronskog mikroskopa, hiperspektralne slike i medicinske CT slike.
Borges, Lucas Rodrigues. "Dose savings in digital breast tomosynthesis through image processing." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/18/18152/tde-02082017-164211/.
Full textEm programas de rastreamento de câncer de mama, a dose de radiação deve ser mantida o mínimo necessário para se alcançar o diagnóstico, para garantir a segurança dos pacientes. Entretanto, imagens adquiridas com dose de radiação reduzida possuem qualidade inferior. Assim, existe um equilíbrio entre a dose de radiação e a qualidade da imagem. Este trabalho propõe um algoritmo de restauração de imagens capaz de recuperar a qualidade das imagens de tomossíntese digital mamária, adquiridas com doses reduzidas de radiação, para alcançar a qualidade de imagens adquiridas com a dose de referência. As contribuições do trabalho incluem a melhoria do modelo de ruído, e a inclusão das características do detector, como o ganho variável do ruído quântico. Para a validação a cadeia de processamento, um método de simulação de redução de dose de radiação foi proposto. Para investigar a possibilidade de redução de dose de radiação utilizada na tomossíntese, um estudo pré-clínico foi conduzido utilizando o método de simulação proposto e a cadeia de processamento. Imagens clínicas de tomossíntese mamária de 72 pacientes foram selecionadas e cinco observadores foram convidados para participar do estudo. Os resultados sugeriram que, após a utilização do processamento proposto, uma redução de 30% de dose de radiação pôde ser alcançada sem que os observadores percebessem diferença nos níveis de ruído e borramento. Assim, o algoritmo de processamento tem o potencial de reduzir os níveis de radiação na tomossíntese mamária, reduzindo também os riscos de indução do câncer de mama.
Facciolo, Furlan Gabriele. "Irregularly sampled image resortation and interpolation." Doctoral thesis, Universitat Pompeu Fabra, 2011. http://hdl.handle.net/10803/22714.
Full textLa generación de modelos urbanos de elevación a partir de imágenes de satélite mediante técnicas de reconstrucción estereoscópica presenta varios retos debido a sus requisitos de precisión. En esta tesis se estudian tres problemas vinculados a la generación de estos modelos partiendo de pares estereoscópicos adquiridos por satélites en una configuración con baseline pequeño. Estos problemas fueron motivados por el proyecto MISS, lanzado por el CNES (Centre National d'Etudes Spatiales) con el objetivo de desarrollar las técnicas de reconstrucción para imágenes adquiridas con baseline pequeños. El primer problema es la restauración de imágenes muestreadas irregularmente y la fusión de imágenes usando un modelo de interpolación de banda limitada. Se propone un nuevo método de restauración, el cual usa una familia de regularizadores que permite controlar el decaimiento espectral de la solución e incorpora el modelo de formación de imagen como un conjunto de restricciones locales. El segundo problema es la interpolación de imágenes muestreadas en forma dispersa usando un prior de auto similitud, se considera también el problema relacionado de inpainting de imágenes. Se propone un nuevo framework para inpainting basado en ejemplares, el cual luego es extendido a la interpolación de imágenes muestreadas en forma dispersa. El tercer problema es la regularización e interpolación de modelos digitales de elevación imponiendo restricciones geométricas las cuales se extraen de una imagen de referencia. Para este problema se estudian tres modelos de regularización: un regularizador anisótropo de superficie mínima, la variación total anisótropa y un nuevo algoritmo de interpolación afín a trozos.
Casaca, Wallace Correa de Oliveira. "Restauração de imagens digitais com texturas utilizando técnicas de decomposição e equações diferenciais parciais /." São José do Rio Preto : [s.n.], 2010. http://hdl.handle.net/11449/94247.
Full textBanca: Evanildo Castro Silva Júnior
Banca: Alagacone Sri Ranga
Resumo: Neste trabalho propomos quatro novas abordagens para tratar o problema de restauração de imagens reais contendo texturas sob a perspectiva dos temas: reconstrução de regiões danificadas, remoção de objetos, e eliminação de ruídos. As duas primeiras abor dagens são designadas para recompor partes perdias ou remover objetos de uma imagem real a partir de formulações envolvendo decomposiçãode imagens e inpainting por exem- plar, enquanto que as duas últimas são empregadas para remover ruído, cujas formulações são baseadas em decomposição de três termos e equações diferenciais parciais não lineares. Resultados experimentais atestam a boa performace dos protótipos apresentados quando comparados à modelagens correlatas da literatura.
Abstract: In this paper we propose four new approaches to address the problem of restoration of real images containing textures from the perspective of reconstruction of damaged areas, object removal, and denoising topics. The first two approaches are designed to reconstruct missing parts or to remove objects of a real image using formulations based on image de composition and exemplar based inpainting, while the last two other approaches are used to remove noise, whose formulations are based on decomposition of three terms and non- linear partial di®erential equations. Experimental results attest to the good performance of the presented prototypes when compared to modeling related in literature.
Mestre
Casaca, Wallace Correa de Oliveira [UNESP]. "Restauração de imagens digitais com texturas utilizando técnicas de decomposição e equações diferenciais parciais." Universidade Estadual Paulista (UNESP), 2010. http://hdl.handle.net/11449/94247.
Full textFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
Neste trabalho propomos quatro novas abordagens para tratar o problema de restauração de imagens reais contendo texturas sob a perspectiva dos temas: reconstrução de regiões danificadas, remoção de objetos, e eliminação de ruídos. As duas primeiras abor dagens são designadas para recompor partes perdias ou remover objetos de uma imagem real a partir de formulações envolvendo decomposiçãode imagens e inpainting por exem- plar, enquanto que as duas últimas são empregadas para remover ruído, cujas formulações são baseadas em decomposição de três termos e equações diferenciais parciais não lineares. Resultados experimentais atestam a boa performace dos protótipos apresentados quando comparados à modelagens correlatas da literatura.
In this paper we propose four new approaches to address the problem of restoration of real images containing textures from the perspective of reconstruction of damaged areas, object removal, and denoising topics. The first two approaches are designed to reconstruct missing parts or to remove objects of a real image using formulations based on image de composition and exemplar based inpainting, while the last two other approaches are used to remove noise, whose formulations are based on decomposition of three terms and non- linear partial di®erential equations. Experimental results attest to the good performance of the presented prototypes when compared to modeling related in literature.
Ferraz, Carolina Toledo. "Uma técnica multimalhas para eliminação de ruídos e retoque digita\"." Universidade de São Paulo, 2006. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-06112006-091437/.
Full textTechniques based on the Well-Balanced Flow Equation have been employed as an efficient tool for edge preserving noise removal. Although effective, this technique demands high computational effort, rendering it not practical in several applications. This work aims at proposing a multigrid-like technique for speeding up the solution of the Well- Balanced Flow equation. In fact, the diffusion equation is solved in a coarse grid and a coarse-to-fine error correction is applied in order to generate the desired solution. The transfer between coarser and finer grids is made by the Mitchell-Filter, a well known interpolation scheme that is designed for preserving edges. Furthermore, the solution of the transport and the Mean Curvature Flow equations is adapted to the multigrid like technique for image inpainting and denoising. Numerical results are compared quantitative and qualitatively with other approaches, showing that our method produces similar image quality with much lower computational time.
McKoen, K. M. H. H. "Digital restoration of low light level video images." Thesis, Imperial College London, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.343720.
Full textSmith, Cameron. "Restoration and registration of digital images using LMS adaptive filters." Thesis, University of the West of Scotland, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.360228.
Full textSantos, Alexander Corrêa dos. "Restauração de imagens de AFM com o funcional de regularização de Tikhonov visando a avaliação de superfícies metálicas." Universidade do Estado do Rio de Janeiro, 2008. http://www.bdtd.uerj.br/tde_busca/arquivo.php?codArquivo=803.
Full textProblemas durante o processo de aquisição de imagens de AFM têm feito com que pesquisas na área de nanotecnologia busquem a utilização de ferramentas para minimizar esses efeitos degenerativos. Neste sentido, foram desenvolvidas ferramentas computacionais de restauração destas imagens degradadas. Neste trabalho é utilizado o método baseado na Regularização de Tikhonov, cuja aplicação está concentrada principalmente em restaurações de imagens biológicas. A proposta deste trabalho é a utilização deste regularizador também em imagens de interesse em engenharia. Em alguns casos, um pré-processamento anteriormente à aplicação do algoritmo, apresenta boa resposta na restauração das imagens. Na fase de préprocessamento foram utilizados alguns filtros como, filtro de média, filtro de mediana, filtro laplaciano e filtro de média pontual. Com a aplicação deste regularizador em imagens foi possível obter perfis de distribuição dos pixels onde é mostrado que na medida em que se aumenta a carga de dissolução de ferro puro em ácido sulfúrico, percebe-se que a razão de aspecto aumenta e características de superfície ficam mais visíveis.
Problems during the process of acquisition of images of AFM have been doing with that research in the nanotechnology searchs the use of tools to minimize those degenerative effects. Computational tools for restoration of these degraded images have developed, in this work the method is used based on Regularization of Tikhonov. This method is usually used for restoration of biological images. It is proposed the use of this regularization functional also in images of interest in engineering. In some cases, a previously processing to the application of the algorithm, it presents good answer in the restoration of the images. The previously processing phase some were used filters as, average filter, median filter, laplacian filter and filter of punctual average, besides combination of filters. With the application of this regularizator it was possible to obtain profiles of distribution of the pixels where is shown that in the measure in that he increases the dissolution charge of iron in sulphuric acid, it is noticed that the aspect reason increases and surface characteristics are more visible.
Rojas, Gómez Renán Alfredo. "Automatic regularization parameter selection for the total variation mixed noise image restoration framework." Master's thesis, Pontificia Universidad Católica del Perú, 2012. http://tesis.pucp.edu.pe/repositorio/handle/123456789/4461.
Full textTesis
D'Ippólito, Karina Miranda. "Estudo de métodos numéricos para eliminação de ruídos em imagens digitais /." São José do Rio Preto : [s.n.], 2005. http://hdl.handle.net/11449/94282.
Full textBanca: Antonio Castelo Filho
Banca: Maurílio Boaventura
Resumo: O objetivo deste trabalho þe apresentar um estudo sobre a aplicação de métodos numéricos para a resolução do modelo proposto por Barcelos, Boaventura e Silva Jr. [7], para a eliminação de ruídos em imagens digitais por meio de uma equação diferencial parcial, e propor uma anþalise da estabilidade do mþetodo iterativo comumente aplicado a este modelo. Uma anþalise comparativa entre os vários mþetodos abordados þe realizada atravþes de resultados experimentais em imagens sintéticas e imagens da vida real.
Abstract: The purpose of this work is to present a study on the application of numerical methods for the resolution of model considered by Barcelos, Boaventura and Silva Jr [7], for image denoising through a partial di erential equation, and to consider a stability analysis of an iterative method usually applied to this model. A comparative analysis among various considered methods is carried out through experimental results for synthetic and real images.
Mestre
LOPES, FILHO Alberto Nicodemus Gomes. "Simulação de forças físicas para segmentação e restauração de dígitos e sequências de dígitos em imagens de documentos manuscritos." Universidade Federal de Pernambuco, 2015. https://repositorio.ufpe.br/handle/123456789/15969.
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Dentre os problemas e desafios que permeiam o processo de digitalização de documentos e todos os passos subsequentes até a transposição da informação para o meio digital, dois pontos específicos são focados: o texto partido ou degradado e texto escrito em tamanha proximidade que geram sobreposições dos traços. Assim, métodos para solucionar tais problemas, foram pesquisados e desenvolvidos. Baseamos nossa abordagem na emulação de forças físicas de inércia e centrípeta pois entendemos que estas podem ser bem utilizadas para o processamento de imagens de caracteres manuscritos. Para o problema de dígitos partidos, foi desenvolvida uma solução para a restauração de dígitos isolados quebrados e de cadeias de dígitos quebrados através da emulação das forças centrípeta e de inércia. Esta solução tem como princípio gerar uma reconstrução da quebra de modo que se assemelhe à escrita do dígito em questão. Também é abordado a sobreposição de pares de dígitos, problema para o qual foi proposta uma solução de segmentação. Esta solução de segmentação se baseia no conceito de uma bola deformável que tem seus movimentos regidos pela emulação da força de inércia e pela deformação que lhe é permitida receber. Ainda, para desenvolvimento e experimentação dos métodos, foram formadas bases de imagens pertinentes a cada aplicação. Os resultados obtidos mostram desempenhos promissores. Ao aplicar a reconstrução, obtivemos um ganho de aproximadamente seis pontos percentuais em taxa de reconhecimento em relação ao reconhecimento dos dígitos partidos. Já a segmentação provou que supera outros dois métodos de segmentação quando aplicamos o reconhecimento aos dígitos segmentados. Também deve-se ressaltar a questão do custo computacional, especificamente a solução voltada para a segmentação de dígitos sobrepostos, onde seu custo se apresenta mais baixo em relação aos métodos similares pesquisados e testados. Assim, mostramos que os métodos propostos atingem seus objetivos, aliando bons desempenhos com custos computacionais baixos.
Among the problems and challenges that surround the process of document digitization and all subsequent steps until the conversion of the information to a digital medium, two specific steps are focused: broken text and text written in such proximity that cause overlapping of strokes. Methods to solve these problems were researched and developed. We base our approach on the emulation of physical forces of inertia and centripetal force, since it is our understanding that the emulation of such forces can be used for the processing of images of handwritten characters and digits. For the problem of broken digits, a solution for the restoration of isolated broken digits and chains of broken digits through the emulations of inertia and centripetal force was developed. This solution has as principle to generate a reconstruction of the break in such a way that it resembles closely the writing style of the digit in question. We also tackle overlapping pairs of digits, problem for which we propose a segmentation solution. This segmentation is based on the concept of a deformable ball that has its movements governed by the emulation of inertia and the degree of deformation the ball is allowed to have. For development and experimentation of the created methods, image databases pertinent to each application were formed. The obtained results show promising performance. When applying the reconstruction, we obtained a gain of approximately six percentage points in recognition rates when compared to rates obtained for broken digits. In regards to segmentation, it proved to outperform two other methods when recognition is applied to the output segmented digits. The computational cost of the methods should also be pointed out, specifically regarding the solution created for the segmentation of overlapped digits, which is lower when compared to other similar methods that were researched and tested. Therefore, we show that the proposed methods reach their goals, coupling performance with low computational costs.
Schindler, Grant. "Unlocking the urban photographic record through 4D scene modeling." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/34719.
Full textD'Ippólito, Karina Miranda [UNESP]. "Estudo de métodos numéricos para eliminação de ruídos em imagens digitais." Universidade Estadual Paulista (UNESP), 2005. http://hdl.handle.net/11449/94282.
Full textConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
O objetivo deste trabalho þe apresentar um estudo sobre a aplicação de métodos numéricos para a resolução do modelo proposto por Barcelos, Boaventura e Silva Jr. [7], para a eliminação de ruídos em imagens digitais por meio de uma equação diferencial parcial, e propor uma anþalise da estabilidade do mþetodo iterativo comumente aplicado a este modelo. Uma anþalise comparativa entre os vários mþetodos abordados þe realizada atravþes de resultados experimentais em imagens sintéticas e imagens da vida real.
The purpose of this work is to present a study on the application of numerical methods for the resolution of model considered by Barcelos, Boaventura and Silva Jr [7], for image denoising through a partial di erential equation, and to consider a stability analysis of an iterative method usually applied to this model. A comparative analysis among various considered methods is carried out through experimental results for synthetic and real images.
Doza, Sajid-Bin. "Riverine Fortress city of "Mahasthan" in deltaic Bengal: in search for the traditional settlement pattern of ancient cities." Doctoral thesis, Universidade de Évora, 2016. http://hdl.handle.net/10174/18416.
Full text"Two approaches to sparsity for image restoration." 2013. http://library.cuhk.edu.hk/record=b5549333.
Full text在第二章中,我們提出了一種創新的算法框架,用於解決信號稀疏假設下的圖像恢復問題。重建圖像的目標函數,由一個數據保真項和`1正則項組成。然而,我們不是直接估計重建的圖像,而是專注於如何獲得重建的這個過程。我們的策略是將這個重建過程表示成基本閾值函數的線性組合(LET):這些線性係數可以通過最小化目標函數解得。然後,可以更新閾值函數并迭代這個過程(i-LET)。這種線性參數化的主要優點是可以大幅降低問題的規模-每次我們只需解決一個線性係數維度大小的優化問題(通常小於十),而不是整個圖像大小的問題。如果閾值函滿足一定的條件,迭代LET算法可以保證全局的收斂性。多個測試圖像在不同噪音水平和不同卷積核類型的測試清楚地表明,我們提出的框架在所需運算時間和迭代循環次數方面,通常超越當今最好水平。
在第三章中,我們擴展了有限創新率採樣框架至某一種特定二維曲線。我們用掩模函數的解來間接定義這個二維曲線。這裡,掩模函數可以表示為有限數目的正弦信號加權求和。因此,從這個角度講,我們定義的二維曲線具有「有限創新率」(FRI)。由於與定義曲線相關聯的指示器圖像沒有帶寬限制,因而根據經典香農採樣定理,不能在有限數量的採樣基礎上獲得完全重建。然而,我們證明,仍然可以設計一個針對指示器圖像採樣的框架,實現完美重構。此外,對於這一方法的空間域解釋,使我們能夠拓展嚴格的FRI曲線模型用於描述自然圖像的邊緣,可以在各種圖像處理的問題中保持圖像的邊緣。我們用一個潛在的在圖像上採樣中的應用作為示例。
Sparsity has played an important role in recent developments of various image restoration techniques. In this MPhil study, we focus on two different types of image restoration problems, which are related by the sparsity assumptions. Specifically, in the first image restoration problem, the signal (i.e. the restored image) itself is sparse in some transformation domain, e.g. wavelet. While in the second part of this study, the signal is not sparse in the traditional sense but that it can be parametrized with a few parameters hence having a sparse representation. Our goal is to tell a "tale of two cities" and to show the connections between the two sparse image restoration problems in this thesis.
In Chapter 2, we proposed a novel algorithmic framework to solve image restoration problems under sparsity assumptions. As usual, the reconstructed image is the minimum of an objective functional that consists of a data fidelity term and an ℓ₁ regularization. However, instead of estimating the reconstructed image that minimizes the objective functional directly, we focus on the restoration process that maps the degraded measurements to the reconstruction. Our idea amounts to parameterizing the process as a linear combination of few elementary thresholding functions (LET) and solve for the linear weighting coefficients by minimizing the objective functional. It is then possible to update the thresholding functions and to iterate this process (i-LET). The key advantage of such a linear parametrization is that the problem size reduces dramatically--each time we only need to solve an optimization problem over the dimension of the linear coefficients (typically less than 10) instead of the whole image dimensio . With the elementary thresholding functions satisfying certain constraints, global convergence of the iterated LET algorithm is guaranteed. Experiments on several test images over a wide range of noise levels and different types of convolution kernels clearly indicate that the proposed framework usually outperform state-of-theart algorithms in terms of both CPU time and number of iterations.
In Chapter 3, we extended the sampling framework for signals with finite rate of innovation to a specific class of two-dimensional curves, which are defined implicitly as the roots of a mask function. Here the mask function has a parametric representation as weighted summation of a finite number of sinusoids, and therefore, has finite rate of innovation [1]. The associated indicator image of the defined curve is not bandlimited and cannot be perfectly reconstructed based on the classical Shannon's sampling theorem. Yet, we show that it is possible to devise a sampling scheme and have a perfect reconstruction from finite number of (noiseless) samples of the indicator image with the annihilating filter method (also known as Prony's method). Robust reconstruction algorithms with noisy samples are also developed. Furthermore, the new spatial domain interpretation of the annihilating filter enables us to generalize the exact FRI curve model to characterize edges of a natural image. We can impose the annihilation constraint to preserve edges in various image processing problems. We exemplified the effectiveness of the annihilation constraint with a potential application in image up-sampling.
Detailed summary in vernacular field only.
Detailed summary in vernacular field only.
Detailed summary in vernacular field only.
Pan, Hanjie.
Thesis (M.Phil.)--Chinese University of Hong Kong, 2013.
Includes bibliographical references (leaves 69-74).
Abstracts also in Chinese.
Acknowledgments --- p.iii
Abstract --- p.vii
Contents --- p.xii
List of Figures --- p.xv
List of Tables --- p.xvii
Chapter 1 --- Introduction --- p.1
Chapter 1.1 --- Sampling Sparse Signals --- p.1
Chapter 1.2 --- Thesis Organizations and Contributions --- p.3
Chapter 2 --- An Iterated Linear Expansion of Thresholds for ℓ₁-based Image Restoration --- p.5
Chapter 2.1 --- Introduction --- p.5
Chapter 2.1.1 --- Problem Description --- p.5
Chapter 2.1.2 --- Approaches to Solve the Problem --- p.6
Chapter 2.1.3 --- Proposed Approach --- p.8
Chapter 2.1.4 --- Organization of the Chapter --- p.9
Chapter 2.2 --- Basic Ingredients --- p.9
Chapter 2.2.1 --- Iterative Reweighted Least Square Methods --- p.9
Chapter 2.2.2 --- Linear Expansion of Thresholds (LET) --- p.11
Chapter 2.3 --- Iterative LET Restoration --- p.15
Chapter 2.3.1 --- Selection of i-LET Bases --- p.15
Chapter 2.3.2 --- Convergence of the i-LET Scheme --- p.16
Chapter 2.3.3 --- Examples of i-LET Bases --- p.18
Chapter 2.4 --- Experimental Results --- p.23
Chapter 2.4.1 --- Deconvolution with Decimated Wavelet Transform --- p.24
Chapter 2.4.2 --- Deconvolution with Redundant Wavelet Transform --- p.28
Chapter 2.4.3 --- Algorithm Complexity Analysis --- p.29
Chapter 2.4.4 --- Choice of Regularization Weight λ --- p.30
Chapter 2.4.5 --- Deconvolution with Cycle Spinnings --- p.30
Chapter 2.5 --- Summary --- p.31
Chapter 3 --- Sampling Curves with Finite Rate of Innovation --- p.33
Chapter 3.1 --- Introduction --- p.33
Chapter 3.2 --- Two-dimensional Curves with Finite Rate of Innovation --- p.34
Chapter 3.2.1 --- FRI Curves --- p.34
Chapter 3.2.2 --- Interior Indicator Image --- p.35
Chapter 3.2.3 --- Acquisition of Indicator Image Samples --- p.36
Chapter 3.3 --- Reconstruction of the Annihilable Curves --- p.37
Chapter 3.3.1 --- Annihilating Filter Method --- p.37
Chapter 3.3.2 --- Relate Fourier Transform with Spatial Domain Samples --- p.39
Chapter 3.3.3 --- Reconstruction of Annihilation Coe cients --- p.39
Chapter 3.3.4 --- Reconstruction with Model Mismatch --- p.42
Chapter 3.3.5 --- Retrieval of the Annihilable Curve Amplitudes --- p.46
Chapter 3.4 --- Dealing with Non-ideal Low-pass Filtered Samples --- p.48
Chapter 3.5 --- Generalization of the FRI Framework for Natural Images --- p.49
Chapter 3.5.1 --- Spatial Domain Interpretation of the Annihilation Equation --- p.50
Chapter 3.5.2 --- Annihilable Curve Approximation of Image Edges --- p.51
Chapter 3.5.3 --- Up-sampling with Annihilation Constraint --- p.53
Chapter 3.6 --- Conclusion --- p.57
Chapter 4 --- Conclusions --- p.59
Chapter 4.1 --- Thesis Summary --- p.59
Chapter 4.2 --- Perspectives --- p.60
Chapter A --- Proofs and Derivations --- p.61
Chapter A.1 --- Proof of Lemma 3 --- p.61
Chapter A.2 --- Proof of Theorem 2 --- p.62
Chapter A.3 --- Efficient Implementation of IRLS Inner Loop with Matlab --- p.63
Chapter A.4 --- Derivations of the Sampling Formula (3.7) --- p.64
Chapter A.5 --- Correspondence between the Spatial and Fourier Domain Samples --- p.65
Chapter A.6 --- Optimal Post-filter Applied to Non-ideal Samples --- p.66
Bibliography --- p.69
"Low frequency coefficient restoration for image coding." 1997. http://library.cuhk.edu.hk/record=b5889086.
Full textThesis (M.Phil.)--Chinese University of Hong Kong, 1997.
Includes bibliographical references (leaves 86-93).
Chapter 1 --- Introduction --- p.1
Chapter 1.1 --- Transform coding and the JPEG scheme --- p.2
Chapter 1.2 --- Motivation --- p.5
Chapter 1.3 --- Thesis outline --- p.6
Chapter 2 --- MED and DC Coefficient Restoration scheme --- p.8
Chapter 2.1 --- Introduction --- p.8
Chapter 2.2 --- MED and DC Coefficient Restoration scheme --- p.10
Chapter 2.2.1 --- Definition --- p.10
Chapter 2.2.2 --- Existing schemes --- p.11
Chapter 2.3 --- DC Coefficient Restoration scheme using block selection scheme --- p.14
Chapter 2.4 --- Joint optimization technique --- p.16
Chapter 2.4.1 --- Lagrange multiplier method --- p.17
Chapter 2.4.2 --- Algorithm description --- p.18
Chapter 2.5 --- Experimental results --- p.20
Chapter 2.6 --- Summary --- p.32
Chapter 3 --- Low Frequency Walsh Transform Coefficient Restoration scheme --- p.34
Chapter 3.1 --- Introduction --- p.34
Chapter 3.2 --- Restoration of low frequency coefficient using Walsh transform --- p.35
Chapter 3.3 --- Selection of quantization table optimized for Walsh transform --- p.37
Chapter 3.3.1 --- Image model used --- p.39
Chapter 3.3.2 --- Infinite uniform quantization --- p.40
Chapter 3.3.3 --- Search for an optimized quantization matrix --- p.42
Chapter 3.4 --- Walsh transform-based LFCR scheme --- p.44
Chapter 3.5 --- Experimental results --- p.46
Chapter 3.6 --- Summary --- p.56
Chapter 4 --- Low Frequency DCT Coefficient Prediction --- p.57
Chapter 4.1 --- Introduction --- p.57
Chapter 4.2 --- Low Frequency Coefficient Prediction scheme with negligible side information --- p.58
Chapter 4.2.1 --- Selection of threshold --- p.63
Chapter 4.2.2 --- Representation of the AC component --- p.63
Chapter 4.3 --- Experimental results --- p.67
Chapter 4.4 --- Summary --- p.84
Chapter 5 --- Conclusions --- p.86
Appendix A --- p.89
Bibliography --- p.90
"DC coefficient restoration for transform image coding." Chinese University of Hong Kong, 1996. http://library.cuhk.edu.hk/record=b5888903.
Full textThesis (M.Phil.)--Chinese University of Hong Kong, 1996.
Includes bibliographical references (leaves 155-[63]).
Acknowledgment --- p.iii
Abstract --- p.iv
Contents --- p.vi
List of Tables --- p.x
List of Figures --- p.xii
Notations --- p.xvii
Chapter 1 --- Introduction --- p.1
Chapter 1.1 --- DC coefficient restoration --- p.1
Chapter 1.2 --- Model based image compression --- p.5
Chapter 1.3 --- The minimum edge difference criterion and the existing estima- tion schemes --- p.7
Chapter 1.3.1 --- Fundamental definitions --- p.8
Chapter 1.3.2 --- The minimum edge difference criterion --- p.9
Chapter 1.3.3 --- The existing estimation schemes --- p.10
Chapter 1.4 --- Thesis outline --- p.14
Chapter 2 --- A mathematical description of the DC coefficient restoration problem --- p.17
Chapter 2.1 --- Introduction --- p.17
Chapter 2.2 --- Mathematical formulation --- p.18
Chapter 2.3 --- Properties of H --- p.22
Chapter 2.4 --- Analysis of the DC coefficient restoration problem --- p.22
Chapter 2.5 --- The MED criterion as an image model --- p.25
Chapter 2.6 --- Summary --- p.27
Chapter 3 --- The global estimation scheme --- p.29
Chapter 3.1 --- Introduction --- p.29
Chapter 3.2 --- the global estimation scheme --- p.30
Chapter 3.3 --- Theory of successive over-relaxation --- p.34
Chapter 3.3.1 --- Introduction --- p.34
Chapter 3.3.2 --- Gauss-Seidel iteration --- p.35
Chapter 3.3.3 --- Theory of successive over-relaxation --- p.38
Chapter 3.3.4 --- Estimation of optimal relaxation parameter --- p.41
Chapter 3.4 --- Using successive over-relaxation in the global estimation scheme --- p.43
Chapter 3.5 --- Experiments --- p.48
Chapter 3.6 --- Summary --- p.49
Chapter 4 --- The block selection scheme --- p.52
Chapter 4.1 --- Introduction --- p.52
Chapter 4.2 --- Failure of the minimum edge difference criterion --- p.53
Chapter 4.3 --- The block selection scheme --- p.55
Chapter 4.4 --- Using successive over-relaxation with the block selection scheme --- p.57
Chapter 4.5 --- Practical considerations --- p.58
Chapter 4.6 --- Experiments --- p.60
Chapter 4.7 --- Summary --- p.61
Chapter 5 --- The edge selection scheme --- p.65
Chapter 5.1 --- Introduction --- p.65
Chapter 5.2 --- Edge information and the MED criterion --- p.66
Chapter 5.3 --- Mathematical formulation --- p.70
Chapter 5.4 --- Practical Considerations --- p.74
Chapter 5.5 --- Experiments --- p.76
Chapter 5.6 --- Discussion of edge selection scheme --- p.78
Chapter 5.7 --- Summary --- p.79
Chapter 6 --- Performance Analysis --- p.81
Chapter 6.1 --- Introduction --- p.81
Chapter 6.2 --- Mathematical derivations --- p.82
Chapter 6.3 --- Simulation results --- p.92
Chapter 6.4 --- Summary --- p.96
Chapter 7 --- The DC coefficient restoration scheme with baseline JPEG --- p.97
Chapter 7.1 --- Introduction --- p.97
Chapter 7.2 --- General specifications --- p.97
Chapter 7.3 --- Simulation results --- p.101
Chapter 7.3.1 --- The global estimation scheme with the block selection scheme --- p.101
Chapter 7.3.2 --- The global estimation scheme with the edge selection scheme --- p.113
Chapter 7.3.3 --- Performance comparison at the same bit rate --- p.121
Chapter 7.4 --- Computation overhead using the DC coefficient restoration scheme --- p.134
Chapter 7.5 --- Summary --- p.134
Chapter 8 --- Conclusions and Discussions --- p.136
Chapter A --- Fundamental definitions --- p.144
Chapter B --- Irreducibility by associated directed graph --- p.146
Chapter B.1 --- Irreducibility and associated directed graph --- p.146
Chapter B.2 --- Derivation of irreducibility --- p.147
Chapter B.3 --- Multiple blocks selection --- p.149
Chapter B.4 --- Irreducibility with edge selection --- p.151
Chapter C --- Sample images --- p.153
Bibliography --- p.155
"Analysis and design of coefficient restoration in image coding." 2000. http://library.cuhk.edu.hk/record=b6073260.
Full text"June 2000."
Thesis (Ph.D.)--Chinese University of Hong Kong, 2000.
Includes bibliographical references (p. 172-177).
Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Mode of access: World Wide Web.
Abstracts in English and Chinese.
"Digital photo album management techniques: from one dimension to multi-dimension." 2005. http://library.cuhk.edu.hk/record=b5892580.
Full textThesis submitted in: November 2004.
Thesis (M.Phil.)--Chinese University of Hong Kong, 2005.
Includes bibliographical references (leaves 96-103).
Abstracts in English and Chinese.
Abstract --- p.i
Acknowledgement --- p.iv
Chapter 1 --- Introduction --- p.1
Chapter 1.1 --- Motivation --- p.1
Chapter 1.2 --- Our Contributions --- p.3
Chapter 1.3 --- Thesis Outline --- p.5
Chapter 2 --- Background Study --- p.7
Chapter 2.1 --- MPEG-7 Introduction --- p.8
Chapter 2.2 --- Image Analysis in CBIR Systems --- p.11
Chapter 2.2.1 --- Color Information --- p.13
Chapter 2.2.2 --- Color Layout --- p.19
Chapter 2.2.3 --- Texture Information --- p.20
Chapter 2.2.4 --- Shape Information --- p.24
Chapter 2.2.5 --- CBIR Systems --- p.26
Chapter 2.3 --- Image Processing in JPEG Frequency Domain --- p.30
Chapter 2.4 --- Photo Album Clustering --- p.33
Chapter 3 --- Feature Extraction and Similarity Analysis --- p.38
Chapter 3.1 --- Feature Set in Frequency Domain --- p.38
Chapter 3.1.1 --- JPEG Frequency Data --- p.39
Chapter 3.1.2 --- Our Feature Set --- p.42
Chapter 3.2 --- Digital Photo Similarity Analysis --- p.43
Chapter 3.2.1 --- Energy Histogram --- p.43
Chapter 3.2.2 --- Photo Distance --- p.45
Chapter 4 --- 1-Dimensional Photo Album Management Techniques --- p.49
Chapter 4.1 --- Photo Album Sorting --- p.50
Chapter 4.2 --- Photo Album Clustering --- p.52
Chapter 4.3 --- Photo Album Compression --- p.56
Chapter 4.3.1 --- Variable IBP frames --- p.56
Chapter 4.3.2 --- Adaptive Search Window --- p.57
Chapter 4.3.3 --- Compression Flow --- p.59
Chapter 4.4 --- Experiments and Performance Evaluations --- p.60
Chapter 5 --- High Dimensional Photo Clustering --- p.67
Chapter 5.1 --- Traditional Clustering Techniques --- p.67
Chapter 5.1.1 --- Hierarchical Clustering --- p.68
Chapter 5.1.2 --- Traditional K-means --- p.71
Chapter 5.2 --- Multidimensional Scaling --- p.74
Chapter 5.2.1 --- Introduction --- p.75
Chapter 5.2.2 --- Classical Scaling --- p.77
Chapter 5.3 --- Our Interactive MDS-based Clustering --- p.80
Chapter 5.3.1 --- Principal Coordinates from MDS --- p.81
Chapter 5.3.2 --- Clustering Scheme --- p.82
Chapter 5.3.3 --- Layout Scheme --- p.84
Chapter 5.4 --- Experiments and Results --- p.87
Chapter 6 --- Conclusions --- p.94
Bibliography --- p.96
Anne-Chao, Chung, and 趙忠安. "Shadow Detection and Restoration on Digital Aerial Images." Thesis, 1999. http://ndltd.ncl.edu.tw/handle/26594071817081149833.
Full text國立中興大學
土木工程學系
87
Image Matching theory of conjugate points on digitial aerial images has been developed since 1950’s,and it tends to be matured today. But there are often faultly matching happening in practical applications. This is because of poor image quality,uniform tones of matching areas and casting shadow. Especially when casting shadow exists,it varies large gray value of image and causes extra diffculty of matching conjugate points on shadow areas. Even though we apply image matching on shadow areas,we are not necessarily get accurate conjugate points. And that is to say nothing of the ability to match accurate conjugate points by automatic Image Matching method. The objectives of this paper are to detect the shadow regions of aerial images,to restore gray value of shadow regions in no shadow-casting conditions,and simultaneously enhance the accuracy of matching. First,we choose shadow areas by manual operations,and then find exact shadow regions in these areas by applying to Image Segmentation method cooperating with Mathematical Morphology theory. Second,we adjust image histograms of shadow regions and restore their gray value in no shadow-casiting conditions by Image Histogram Matching method. Finally,we apply image matching of conjugate points in shadow regions of two stereo overlapping imges respectively before and after shadow restoration processes. That will assist us to examine the ability of enhancing accuracy of image matching in aerial shadow areas,and it can also demostrate the objectives of this paper.