This master’s thesis deals with issues, which are suitable to solve by the method of adaptive filtering of additive noise in image processing. It deduces an algorithm of the adaptive filtering method. Then it studies properties of this filter. In the end it applies deduced algorithm on a particular picture and compares the results with linear filtering.

Les travaux de cette thèse portent sur l'égalisation des canaux de transmission pour des modulations mono-porteuses et multi-porteuses. Dans le cadre de l'égalisation, nous nous intéressons, plus précisément, à l'égalisation aveugle. Tout d'abord, nous décrivons les différents éléments constituants une chaîne de communication, et les différents types de modulations mono-porteuses et muti-porteuses (OFDM). Ensuite, nous faisons un état de l'art sur les méthodes de l'égalisation aveugle pour une modulation mono-porteuse. Nous proposons par la suite un algorithme d'égalisation aveugle en présence de perturbations bornées. Ensuite, nous fournissons une analyse de stabilité et de convergence de l'algorithme proposé. Dans le cadre de la modulation multi-porteuse, nous présentons, dans un premier temps, un état de l'art sur les techniques d'égalisation aveugle pour le système OFDM. Ensuite, nous adaptons l'algorithme proposé pour le système OFDM pour des canaux à trajets multiples, en particulier les canaux Raleigh et Rice. Les performances de l'algorithme proposé sont illustrées à travers plusieurs exemples en simulation tout au long de la thèse. / The work of this thesis deals with the equalization of the transmission channels for a single-carrier and multi-carrier modulation. In the context of equalization, we focus precisely on the blind equalization. First, we give a description of various elements constituting a communication chain, a description of different types of single-carrier modulations and a description of a multi-carrier modulation (OFDM). Then, we give an overview of the blind equalization methods for a single-carrier modulation. We propose subsequently a blind equalization algorithm in the presence of a bounded perturbation. Next, we provide stability and convergence analysis of the proposed method. In the context of multi-carrier modulation, we first present an overview of the blind equalization techniques for the OFDM system. Next, we adapt the proposed method for the OFDM system under multipath channels, especially the Raleigh and the Rice channels. Performance of the proposed algorithm have been illustrated in simulation by considering many examples throughout this thesis.

Nas últimas décadas, diversos sistemas de comunicação baseados em caos foram propostos. Dentre eles, vários utilizam uma função para codificar uma mensagem em um sinal caótico, que é caracterizado como um sinal de banda larga. Dado que o canal de transmissão é limitado em banda por natureza, é necessário determinar e controlar o espectro do sinal caótico transmitido por esse sistema. Nesse sentido, um sistema de comunicação em banda limitada, baseado em sincronismo caótico, foi proposto recentemente utilizando-se filtros digitais para controlar a largura de banda dos sinais transmitidos. Esses filtros, inseridos no sistema de comunicação, modificam o sistema original gerador do sinal caótico, tornando-se necessário analisar como essa inserção afeta o sincronismo caótico. Nessa tese, apresenta-se uma análise desse sistema de comunicação digital de tempo discreto, baseado em sincronismo caótico, considerando-se um canal com ruído aditivo branco gaussiano. As condições necessárias para a sincronização desse sistema são obtidas analiticamente, por meio de um teorema, para um mapa gerador de caos qualquer. O desempenho desse sistema é avaliado em termos da taxa de erro de bit, e, para melhorar seu desempenho, propõe-se filtrar o ruído fora da banda do sinal na entrada do receptor. Apesar das condições de sincronismo terem sido determinadas, a inserção dos filtros também pode modificar a natureza caótica dos sinais, e não há garantia que os sinais transmitidos sejam caóticos. Para analisar a natureza caótica dos sinais transmitidos pelo sistema de comunicação, o maior expoente de Lyapunov é obtido numericamente em função dos coeficientes dos filtros, dos parâmetros do mapa e da função de codificação da mensagem. / In recent decades, several chaos-based communication systems have been proposed. Many of them use a function to encode a message into a chaotic signal, which is characterized as wideband. Since every transmission channel is bandlimited in nature, it is necessary to determine and to control the spectrum of the chaotic signal transmitted by this system. This way, a bandlimited chaos-based communication system was recently proposed using digital filters and chaotic synchronization. These filters, inserted in the communication system, modify the original chaotic generator system, becoming necessary to study how their insertion affect chaotic synchronization. In this work, we present an analysis of this discrete-time chaos-based digital communication system considering an additive white Gaussian noise channel. The synchronization conditions of this system is analytically obtained, through a theorem, for a generic chaos generator map. The system performance is evaluated in terms of bit error rate, and, to obtain a performance improvement, it is also proposed to filter the out-of-band noise in the receiver. Although the conditions for chaotic synchronization have been determined, the filters insertion can also modify the chaotic nature of the signals, and there is no guarantee that the transmitted signals remain chaotic. To analyze the chaotic nature of the communication system transmitted signals, the largest Lyapunov exponent is numerically accessed as a function of the filters coefficients, the parameters of the map and the message coding function.

Nas últimas décadas, diversos sistemas de comunicação baseados em caos foram propostos. Dentre eles, vários utilizam uma função para codificar uma mensagem em um sinal caótico, que é caracterizado como um sinal de banda larga. Dado que o canal de transmissão é limitado em banda por natureza, é necessário determinar e controlar o espectro do sinal caótico transmitido por esse sistema. Nesse sentido, um sistema de comunicação em banda limitada, baseado em sincronismo caótico, foi proposto recentemente utilizando-se filtros digitais para controlar a largura de banda dos sinais transmitidos. Esses filtros, inseridos no sistema de comunicação, modificam o sistema original gerador do sinal caótico, tornando-se necessário analisar como essa inserção afeta o sincronismo caótico. Nessa tese, apresenta-se uma análise desse sistema de comunicação digital de tempo discreto, baseado em sincronismo caótico, considerando-se um canal com ruído aditivo branco gaussiano. As condições necessárias para a sincronização desse sistema são obtidas analiticamente, por meio de um teorema, para um mapa gerador de caos qualquer. O desempenho desse sistema é avaliado em termos da taxa de erro de bit, e, para melhorar seu desempenho, propõe-se filtrar o ruído fora da banda do sinal na entrada do receptor. Apesar das condições de sincronismo terem sido determinadas, a inserção dos filtros também pode modificar a natureza caótica dos sinais, e não há garantia que os sinais transmitidos sejam caóticos. Para analisar a natureza caótica dos sinais transmitidos pelo sistema de comunicação, o maior expoente de Lyapunov é obtido numericamente em função dos coeficientes dos filtros, dos parâmetros do mapa e da função de codificação da mensagem. / In recent decades, several chaos-based communication systems have been proposed. Many of them use a function to encode a message into a chaotic signal, which is characterized as wideband. Since every transmission channel is bandlimited in nature, it is necessary to determine and to control the spectrum of the chaotic signal transmitted by this system. This way, a bandlimited chaos-based communication system was recently proposed using digital filters and chaotic synchronization. These filters, inserted in the communication system, modify the original chaotic generator system, becoming necessary to study how their insertion affect chaotic synchronization. In this work, we present an analysis of this discrete-time chaos-based digital communication system considering an additive white Gaussian noise channel. The synchronization conditions of this system is analytically obtained, through a theorem, for a generic chaos generator map. The system performance is evaluated in terms of bit error rate, and, to obtain a performance improvement, it is also proposed to filter the out-of-band noise in the receiver. Although the conditions for chaotic synchronization have been determined, the filters insertion can also modify the chaotic nature of the signals, and there is no guarantee that the transmitted signals remain chaotic. To analyze the chaotic nature of the communication system transmitted signals, the largest Lyapunov exponent is numerically accessed as a function of the filters coefficients, the parameters of the map and the message coding function.

This thesis presents a study on time series analysis, which was conducted based on the following hypothesis: time series influenced by additive noise can be decomposed into stochastic and deterministic components in which individual models permit obtaining a hybrid one that improves accuracy. This hypothesis was confirmed in two steps. In the first one, we developed a formal analysis using the Nyquist-Shannon sampling theorem, proving Intrinsic Mode Functions (IMFs) extracted from the Empirical Mode Decomposition (EMD) method can be combined, according to their frequency intensities, to form stochastic and deterministic components. Considering this proof, we designed two approaches to decompose time series, which were evaluated in synthetic and real-world scenarios. Experimental results confirmed the importance of decomposing time series and individually modeling the deterministic and stochastic components, proving the second part of our hypothesis. Furthermore, we noticed the individual analysis of both components plays an important role in detecting patterns and extracting implicit information from time series. In addition to these approaches, this thesis also presents two new measurements. The first one is used to evaluate the accuracy of time series modeling in forecasting observations. This measurement was motivated by the fact that existing measurements only consider the perfect match between expected and predicted values. This new measurement overcomes this issue by also analyzing the global time series behavior. The second measurement presented important results to assess the influence of the deterministic and stochastic components on time series observations, supporting the decomposition process. Finally, this thesis also presents a Systematic Literature Review, which collected important information on related work, and two new methods to produce surrogate data, which permit investigating the presence of linear and nonlinear Gaussian processes in time series, irrespective of the influence of nonstationary behavior / Esta tese apresenta um estudo sobre análise de séries temporais, a qual foi conduzida baseada na seguinte hipótese: séries temporais influenciadas por ruído aditivo podem ser decompostas em componentes estocásticos e determinísticos que ao serem modelados individualmente permitem obter um modelo híbrido de maior acurácia. Essa hipótese foi confirmada em duas etapas. Na primeira, desenvolveu-se uma análise formal usando o teorema de amostragem proposto por Nyquist-Shannon, provando que IMFs (Intrinsic Mode Functions) extraídas pelo método EMD (Empirical Mode Decomposition) podem ser combinadas de acordo com suas intensidades de frequência para formar os componentes estocásticos e determinísticos. Considerando essa prova, duas abordagens de decomposição de séries foram desenvolvidas e avaliadas em aplicações sintéticas e reais. Resultados experimentais confirmaram a importância de decompor séries temporais e modelar seus componentes estocásticos e determinísticos, provando a segunda parte da hipótese. Além disso, notou-se que a análise individual desses componentes possibilita detectar padrões e extrair importantes informações implícitas em séries temporais. Essa tese apresenta ainda duas novas medidas. A primeira é usada para avaliar a acurácia de modelos utilizados para predizer observações. A principal vantagem dessa medida em relação às existentes é a possibilidade de avaliar os valores individuais de predição e o comportamento global entre as observações preditas e experadas. A segunda medida permite avaliar a influência dos componentes estocásticos e determinísticos sobre as séries temporais. Finalmente, essa tese apresenta ainda resultados obtidos por meio de uma revisão sistemática da literatura, a qual coletou importantes trabalhos relacionados, e dois novos métodos para geração de dados substitutos, permitindo investigar a presença de processos Gaussianos lineares e não-lineares, independente da influência de comportamento não-estacionário

<p>In this thesis we study a scalar uniform and non-uniform quantization of random processes (or signals) in average case setting. Quantization (or discretization) of a signal is a standard task in all nalog/digital devices (e.g., digital recorders, remote sensors etc.). We evaluate the necessary memory capacity (or quantization rate) needed for quantized process realizations by exploiting the correlation structure of the model random process. The thesis consists of an introductory survey of the subject and related theory followed by four included papers (A-D).</p><p>In Paper A we develop a quantization coding method when quantization levels crossings by a process realization are used for its coding. Asymptotical behavior of mean quantization rate is investigated in terms of the correlation structure of the original process. For uniform and non-uniform quantization, we assume that the quantization cellwidth tends to zero and the number of quantization levels tends to infinity, respectively.</p><p>In Papers B and C we focus on an additive noise model for a quantized random process. Stochastic structures of asymptotic quantization errors are derived for some bounded and unbounded non-uniform quantizers when the number of quantization levels tends to infinity. The obtained results can be applied, for instance, to some optimization design problems for quantization levels.</p><p>Random signals are quantized at sampling points with further compression. In Paper D the concern is statistical inference for run-length encoding (RLE) method, one of the compression techniques, applied to quantized stationary Gaussian sequences. This compression method is widely used, for instance, in digital signal and image processing. First, we deal with mean RLE quantization rates for various probabilistic models. For a time series with unknown stochastic structure, we investigate asymptotic properties (e.g., asymptotic normality) of two estimates for the mean RLE quantization rate based on an observed sample when the sample size tends to infinity.</p><p>These results can be used in communication theory, signal processing, coding, and compression applications. Some examples and numerical experiments demonstrating applications of the obtained results for synthetic and real data are presented.</p>

In this thesis we study a scalar uniform and non-uniform quantization of random processes (or signals) in average case setting. Quantization (or discretization) of a signal is a standard task in all nalog/digital devices (e.g., digital recorders, remote sensors etc.). We evaluate the necessary memory capacity (or quantization rate) needed for quantized process realizations by exploiting the correlation structure of the model random process. The thesis consists of an introductory survey of the subject and related theory followed by four included papers (A-D). In Paper A we develop a quantization coding method when quantization levels crossings by a process realization are used for its coding. Asymptotical behavior of mean quantization rate is investigated in terms of the correlation structure of the original process. For uniform and non-uniform quantization, we assume that the quantization cellwidth tends to zero and the number of quantization levels tends to infinity, respectively. In Papers B and C we focus on an additive noise model for a quantized random process. Stochastic structures of asymptotic quantization errors are derived for some bounded and unbounded non-uniform quantizers when the number of quantization levels tends to infinity. The obtained results can be applied, for instance, to some optimization design problems for quantization levels. Random signals are quantized at sampling points with further compression. In Paper D the concern is statistical inference for run-length encoding (RLE) method, one of the compression techniques, applied to quantized stationary Gaussian sequences. This compression method is widely used, for instance, in digital signal and image processing. First, we deal with mean RLE quantization rates for various probabilistic models. For a time series with unknown stochastic structure, we investigate asymptotic properties (e.g., asymptotic normality) of two estimates for the mean RLE quantization rate based on an observed sample when the sample size tends to infinity. These results can be used in communication theory, signal processing, coding, and compression applications. Some examples and numerical experiments demonstrating applications of the obtained results for synthetic and real data are presented.

This thesis presents a study on time series analysis, which was conducted based on the following hypothesis: time series influenced by additive noise can be decomposed into stochastic and deterministic components in which individual models permit obtaining a hybrid one that improves accuracy. This hypothesis was confirmed in two steps. In the first one, we developed a formal analysis using the Nyquist-Shannon sampling theorem, proving Intrinsic Mode Functions (IMFs) extracted from the Empirical Mode Decomposition (EMD) method can be combined, according to their frequency intensities, to form stochastic and deterministic components. Considering this proof, we designed two approaches to decompose time series, which were evaluated in synthetic and real-world scenarios. Experimental results confirmed the importance of decomposing time series and individually modeling the deterministic and stochastic components, proving the second part of our hypothesis. Furthermore, we noticed the individual analysis of both components plays an important role in detecting patterns and extracting implicit information from time series. In addition to these approaches, this thesis also presents two new measurements. The first one is used to evaluate the accuracy of time series modeling in forecasting observations. This measurement was motivated by the fact that existing measurements only consider the perfect match between expected and predicted values. This new measurement overcomes this issue by also analyzing the global time series behavior. The second measurement presented important results to assess the influence of the deterministic and stochastic components on time series observations, supporting the decomposition process. Finally, this thesis also presents a Systematic Literature Review, which collected important information on related work, and two new methods to produce surrogate data, which permit investigating the presence of linear and nonlinear Gaussian processes in time series, irrespective of the influence of nonstationary behavior / Esta tese apresenta um estudo sobre análise de séries temporais, a qual foi conduzida baseada na seguinte hipótese: séries temporais influenciadas por ruído aditivo podem ser decompostas em componentes estocásticos e determinísticos que ao serem modelados individualmente permitem obter um modelo híbrido de maior acurácia. Essa hipótese foi confirmada em duas etapas. Na primeira, desenvolveu-se uma análise formal usando o teorema de amostragem proposto por Nyquist-Shannon, provando que IMFs (Intrinsic Mode Functions) extraídas pelo método EMD (Empirical Mode Decomposition) podem ser combinadas de acordo com suas intensidades de frequência para formar os componentes estocásticos e determinísticos. Considerando essa prova, duas abordagens de decomposição de séries foram desenvolvidas e avaliadas em aplicações sintéticas e reais. Resultados experimentais confirmaram a importância de decompor séries temporais e modelar seus componentes estocásticos e determinísticos, provando a segunda parte da hipótese. Além disso, notou-se que a análise individual desses componentes possibilita detectar padrões e extrair importantes informações implícitas em séries temporais. Essa tese apresenta ainda duas novas medidas. A primeira é usada para avaliar a acurácia de modelos utilizados para predizer observações. A principal vantagem dessa medida em relação às existentes é a possibilidade de avaliar os valores individuais de predição e o comportamento global entre as observações preditas e experadas. A segunda medida permite avaliar a influência dos componentes estocásticos e determinísticos sobre as séries temporais. Finalmente, essa tese apresenta ainda resultados obtidos por meio de uma revisão sistemática da literatura, a qual coletou importantes trabalhos relacionados, e dois novos métodos para geração de dados substitutos, permitindo investigar a presença de processos Gaussianos lineares e não-lineares, independente da influência de comportamento não-estacionário

Práce se zabývá adaptivními filtry pro vizualizaci obrazů s vysokým rozlišením. V teoretické části je popsán princip činnosti konfokálního mikroskopu a matematicky korektně zaveden pojem digitální obraz. Pro zpracování obrazů je volen jak frekvenční přístup (s využitím 2-D a 3-D diskrétní Fourierovy transformace a frekvenčních filtrů), tak přístup pomocí digitální geometrie (s využitím adaptivní ekvalizace histogramu s adaptivním okolím). Dále jsou popsány potřebné úpravy pro práci s neideálními obrazy obsahujícími aditivní a impulzní šum. Závěr práce se věnuje prostorové rekonstrukci objektů na základě jejich optických řezů. Veškeré postupy a algoritmy jsou i prakticky zpracovány v softwaru, který byl vyvinut v rámci této práce.

Nous proposons dans cette thèse de développer une méthode de restauration aveugle d'images flouées et bruitées où aucune connaissance a priori n'est exigée. Ce manuscrit est composé de trois chapitres : le 1er chapitre est consacré aux travaux de l'état de l'art. Les approches d'optimisation pour la résolution du problème de restauration y sont d'abord discutées. Ensuite les principales méthodes de restauration, dites semi-aveugles car nécessitant un minimum de connaissance a priori sont analysées. Parmi ces méthodes, cinq sont retenues pour évaluation. Le 2ème chapitre est dédié à la comparaison des performances des méthodes retenues dans le chapitre précédent. Les principaux critères objectifs d'évaluation de la qualité des images restaurées sont présentés. Parmi ces critères, la norme L1 de l'erreur d'estimation est sélectionnée. L'étude comparative menée sur une banque d'images monochromes, dégradées artificiellement par deux fonctions floues de supports différents et trois niveaux de bruit a permis de mettre en évidence les deux méthodes les plus pertinentes. La première repose sur une approche alternée mono-échelle où la PSF et l'image sont estimées dans une seule étape. La seconde utilise une approche hybride multi-échelle qui consiste tout d'abord à estimer de manière alternée la PSF et une image latente, puis dans une étape suivante séquentielle, à restaurer l'image. Dans l'étude comparative conduite, l'avantage revient à cette dernière. Les performances de ces méthodes serviront de référence pour comparer ensuite la méthode développée. Le 3ème chapitre porte sur la méthode développée. Nous avons cherché à rendre aveugle l'approche hybride retenue dans le chapitre précédent tout en améliorant la qualité d'estimation de la PSF et de l'image restaurée. Les contributions ont porté sur plusieurs points. Une première série d'améliorations concerne la redéfinition des échelles, celle de l'initialisation de l'image latente à chaque niveau d'échelle, l'évolution des paramètres pour la sélection des contours pertinents servant de support à l'estimation de la PSF et enfin, la définition d'un critère d'arrêt aveugle. Une seconde série de contributions a porté sur l'estimation aveugle des deux paramètres de régularisation impliqués pour éviter d'avoir à les fixer empiriquement. Chaque paramètre est associé à une fonction coût distincte l'une pour l'estimation de la PSF et la seconde pour l'estimation d'une image latente. Dans l'étape séquentielle qui suit, nous avons cherché à affiner le support de la PSF estimée dans l'étape alternée, avant de l'exploiter dans le processus de restauration de l'image. A ce niveau, la seule connaissance a priori nécessaire est une borne supérieure du support de la PSF. Les différentes évaluations conduites sur des images monochromes et hyperspectrales dégradées artificiellement par plusieurs flous de type mouvement, de supports différents, montrent une nette amélioration de la qualité de restauration obtenue par l'approche développée par rapport aux deux meilleures approches de l'état de l'art retenues. / We propose in this thesis manuscript to develop a blind restoration method of single component blurred and noisy images where no prior knowledge is required. This manuscript is composed of three chapters: the first chapter focuses on state-of-art works. The optimization approaches for resolving the restoration problem are discussed first. Then, the main methods of restoration, so-called semi-blind ones because requiring a minimum of a priori knowledge are analysed. Five of these methods are selected for evaluation. The second chapter is devoted to comparing the performance of the methods selected in the previous chapter. The main objective criteria for evaluating the quality of the restored images are presented. Of these criteria, the l1 norm for the estimation error is selected. The comparative study conducted on a database of monochromatic images, artificially degraded by two blurred functions with different support size and three levels of noise, revealed the most two relevant methods. The first one is based on a single-scale alternating approach where both the PSF and the image are estimated alternatively. The second one uses a multi-scale hybrid approach, which consists first of alternatingly estimating the PSF and a latent image, then in a sequential next step, restoring the image. In the comparative study performed, the benefit goes to the latter. The performance of both these methods will be used as references to then compare the newly designed method. The third chapter deals with the developed method. We have sought to make the hybrid approach retained in the previous chapter as blind as possible while improving the quality of estimation of both the PSF and the restored image. The contributions covers a number of points. A first series concerns the redefinition of the scales that of the initialization of the latent image at each scale level, the evolution of the parameters for the selection of the relevant contours supporting the estimation of the PSF and finally the definition of a blind stop criterion. A second series of contributions concentrates on the blind estimation of the two regularization parameters involved in order to avoid having to fix them empirically. Each parameter is associated with a separate cost function either for the PSF estimation or for the estimation of a latent image. In the sequential step that follows, we refine the estimation of the support of the PSF estimated in the previous alternated step, before exploiting it in the process of restoring the image. At this level, the only a priori knowledge necessary is a higher bound of the support of the PSF. The different evaluations performed on monochromatic and hyperspectral images artificially degraded by several motion-type blurs with different support sizes, show a clear improvement in the quality of restoration obtained by the newly designed method in comparison to the best two state-of-the-art methods retained.