Thesis (M. Phil.)--University of Hong Kong, 1995. / Includes bibliographical references.

Thèse (M.Eng.) -- Université du Québec à Chicoutimi, 2005. / Bibliogr.: f. 116-119. Document électronique également accessible en format PDF. CaQCU

Thesis (M.App.Sc.) - Carleton University, 2007. / Includes bibliographical references (p. 168-170). Also available in electronic format on the Internet.

No description available.

The Iterative Closest Point (ICP) algorithm has been an extremely popular method for 3D points or surface registration. Given two point sets, it simultaneously solves for correspondences and estimates the motion between these two point sets. However, by only registering two such views at a time, ICP fails to exploit the redundant information available in multiple views that have overlapping regions. In this thesis, a multiview extension of the ICP algorithm is provided that simultaneously averages the redundant information available in the views with overlapping regions. Variants of this method that carry out such simultaneous registration in a causal manner and that utilize the transitivity property of point correspondences are also provided. The improved accuracy in registration of these motion averaged approaches in comparison with the conventional ICP method is established through extensive experiments. In addition, the motion averaged approaches are compared with the existing multiview techniques of Bergevin et. al. and Benjemaa et. al. The results of the methods applied to the Happy Buddha and the Stanford Bunny datasets of 3D Stanford repository and to the Pooh and the Bunny datasets of the Ohio (MSU/WSU) Range Image database are also presented.

Dû à la complexité des algorithmes de traitement d’images récents et dans le but d'accélérer la procédure de la conception des MPSoCs, méthodologies de prototypage rapide sont nécessaires pour fournir différents choix pour le programmeur de générer des programmes parallèles efficaces. Ce manuscrit présente les travaux menés pour proposer une méthodologie de prototypage rapide permettant la conception des architectures MPSOC ainsi que la génération automatique de système matériel / logiciel dédié un circuit reprogrammable (FPGA). Pour faciliter la programmation parallèle, l'approche MPSoC proposée est basée sur l’utilisation de Framework « CubeGen » qui permet la génération des différentes solutions envisageables pour réaliser des prototypes dans le domaine du traitement d’image. Ce document décrit une méthode basée sur le concept des squelettes générés en fonction des caractéristiques d'application afin d'exploiter tous les types de parallélisme des algorithmes réels. Un ensemble d’expérimentations utilisant des algorithmes courants permet d’évaluer les performances du flot de conception proposé équivalente à une architecture basé des processeurs hardcore et les solutions traditionnels basé sur cibles ASIC. / Due to the complexity of image processing algorithms and the restrictions imposed by MPSoC designs to reach their full potentials, automatic design methodologies are needed to provide guidance for the programmer to generate efficient parallel programs. In this dissertation, we present a MPSoC-based design methodology solution supporting automatic design space exploration, automatic performance evaluation, as well as automatic hardware/software system generation. To facilitate the parallel programming, the presented MPSoC approach is based on a CubeGen framework that permits the expression of different scenarios for architecture and algorithmic design exploring to reach the desired level of performance, resulting in short time development. The generated design could be implemented in a FPGA technology with an expected improvement in application performance and power consumption. Starting from the application, we have evolved our effective methodology to provide several parameterizable algorithmic skeletons in the face of varying application characteristics to exploit all types of parallelism of the real algorithms. Implementing such applications on our parallel embedded system shows that our advanced methods achieve increased efficiency with respect to the computational and communication requirements. The experimental results demonstrate that the designed multiprocessing architecture can be programmed efficiently and also can have an equivalent performance to a more powerful designs based hard-core processors and better than traditional ASIC solutions which are too slow and too expensive.

Uma área de intensa atividade de pesquisa em nanotecnologia está relacionada à restauração de imagens obtidas através dos microscópios de força atômica (AFM). Durante o processo de aquisição as imagens de AFM estão sujeitas às limitações impostas pela instrumentação utilizada e costumam apresentar pobres relações sinal/ruído, bem como a manifestação dos efeitos degenerativos relacionados à interação entre o tip e a amostra. Buscando tratar imagens obtidas de estruturas biológicas, tem sido propostos e testados diversos algoritmos de restauração, e nesta dissertação é utilizado um método baseado na Regularização de Tikhonov. Ao longo do desenvolvimento de diversos algoritmos de restauração foi observado que os indicadores matemáticos usuais para avaliação de desempenho não correspondiam à percepção visual relativa às imagens restauradas. Este trabalho propõe e avalia diferentes indicadores de desempenho para algoritmos de restauração utilizados no pósprocessamento de imagens obtidas em escala nanométrica por microscopia de força atômica e imagens artificiais criadas especialmente para testar o indicador de desempenho utilizado. São investigados indicadores usuais empregados em restauração de imagens, sendo também proposta a implementação de indicadores baseado nas distâncias de Bregman. O trabalho foi dividido em duas partes. Primeiramente foi gerado e restaurado um conjunto de imagens utilizando o funcional de regularização de Tikhonov, sendo distribuídas entre 50 pessoas que foram chamadas de avaliadores humanos. A tarefa consistia em avaliar as imagens, procurando identificar o quanto as imagens restauradas se aproximavam das imagens originais, no que se relaciona à visão humana. A segunda parte consistiu na implementação de uma rotina computacional para o cálculo de vários indicadores matemáticos. Posteriormente foi realizada a comparação dos resultados obtidos através dos indicadores matemáticos com a percepção visual dos avaliadores humanos, sendo esta última essencialmente qualitativa, sendo então transformada em uma escala numérica para permitir então a comparação com os indicadores matemáticos. Observou-se que dependendo dos parâmetros utilizados no algoritmo de restauração baseado no funcional de regularização de Tikhonov e dos tipos de imagens restauradas, os indicadores baseados nas Distâncias de Bregman apresentam melhores resultados do que aqueles obtidos com indicadores tradicionais, como por exemplo o erro médio quadrático (MSE Mean Square Error), levando a uma concordância maior destes resultados quando comparados com a avaliação feita pelos avaliadores humanos. / The restoration of images acquired with Atomic Force Microscopes (AFM) consists on a very intense research area in nanotechnology. During the acquisition process the AFM images are subjected to the constraints imposed by the experimental apparatus usually presenting poor signal to noise ratios as well as the effects of tip-sample interaction. In order to process images related to biological structures, several restoration algorithms have been proposed and tested, and in the present dissertation is used a method based in Tikhonovs regularization. Throughout the development of several restoration algorithms it has been observed that the usual performance measures did not correspond to the human visual perception of the restored images. In the present dissertation are proposed and evaluated several performance measures for restoration algorithms used in the post-processing of images acquired in nanoscale with AFM as well as artificial images created in order to test the performance measure used. Usually used performance measures are investigated as well as measures based on Bregman distances. The research was conducted in two parts. First a set of images was generated and restored using Tikhonovs regularization functional, being then distributed to 50 human referees. Their task consisted in evaluating the images in order to grade how close the restored images were to the original images, in respect to human visual perception. The second part of the research consisted in the implementation of a computational program to perform the computation of the mathematical performance measures. Afterwards a comparison was performed of the mathematical performance measures with respect to the visual perception of the human referees, being the latter essentially qualitative which was then transformed in a numerical scale in order to allow the comparison with the mathematical measures. It was observed that depending on the parameters used in the restoration algorithm based in Tikhonovs regularization functional and the type of the restored image, the mathematical performance measures based on Bregman distances present better results than those obtained with other usual performance measures such as the Mean Square Error (MSE) yielding to a better agreement with the evaluation performed by the human referees.

Uma área de intensa atividade de pesquisa em nanotecnologia está relacionada à restauração de imagens obtidas através dos microscópios de força atômica (AFM). Durante o processo de aquisição as imagens de AFM estão sujeitas às limitações impostas pela instrumentação utilizada e costumam apresentar pobres relações sinal/ruído, bem como a manifestação dos efeitos degenerativos relacionados à interação entre o tip e a amostra. Buscando tratar imagens obtidas de estruturas biológicas, tem sido propostos e testados diversos algoritmos de restauração, e nesta dissertação é utilizado um método baseado na Regularização de Tikhonov. Ao longo do desenvolvimento de diversos algoritmos de restauração foi observado que os indicadores matemáticos usuais para avaliação de desempenho não correspondiam à percepção visual relativa às imagens restauradas. Este trabalho propõe e avalia diferentes indicadores de desempenho para algoritmos de restauração utilizados no pósprocessamento de imagens obtidas em escala nanométrica por microscopia de força atômica e imagens artificiais criadas especialmente para testar o indicador de desempenho utilizado. São investigados indicadores usuais empregados em restauração de imagens, sendo também proposta a implementação de indicadores baseado nas distâncias de Bregman. O trabalho foi dividido em duas partes. Primeiramente foi gerado e restaurado um conjunto de imagens utilizando o funcional de regularização de Tikhonov, sendo distribuídas entre 50 pessoas que foram chamadas de avaliadores humanos. A tarefa consistia em avaliar as imagens, procurando identificar o quanto as imagens restauradas se aproximavam das imagens originais, no que se relaciona à visão humana. A segunda parte consistiu na implementação de uma rotina computacional para o cálculo de vários indicadores matemáticos. Posteriormente foi realizada a comparação dos resultados obtidos através dos indicadores matemáticos com a percepção visual dos avaliadores humanos, sendo esta última essencialmente qualitativa, sendo então transformada em uma escala numérica para permitir então a comparação com os indicadores matemáticos. Observou-se que dependendo dos parâmetros utilizados no algoritmo de restauração baseado no funcional de regularização de Tikhonov e dos tipos de imagens restauradas, os indicadores baseados nas Distâncias de Bregman apresentam melhores resultados do que aqueles obtidos com indicadores tradicionais, como por exemplo o erro médio quadrático (MSE Mean Square Error), levando a uma concordância maior destes resultados quando comparados com a avaliação feita pelos avaliadores humanos. / The restoration of images acquired with Atomic Force Microscopes (AFM) consists on a very intense research area in nanotechnology. During the acquisition process the AFM images are subjected to the constraints imposed by the experimental apparatus usually presenting poor signal to noise ratios as well as the effects of tip-sample interaction. In order to process images related to biological structures, several restoration algorithms have been proposed and tested, and in the present dissertation is used a method based in Tikhonovs regularization. Throughout the development of several restoration algorithms it has been observed that the usual performance measures did not correspond to the human visual perception of the restored images. In the present dissertation are proposed and evaluated several performance measures for restoration algorithms used in the post-processing of images acquired in nanoscale with AFM as well as artificial images created in order to test the performance measure used. Usually used performance measures are investigated as well as measures based on Bregman distances. The research was conducted in two parts. First a set of images was generated and restored using Tikhonovs regularization functional, being then distributed to 50 human referees. Their task consisted in evaluating the images in order to grade how close the restored images were to the original images, in respect to human visual perception. The second part of the research consisted in the implementation of a computational program to perform the computation of the mathematical performance measures. Afterwards a comparison was performed of the mathematical performance measures with respect to the visual perception of the human referees, being the latter essentially qualitative which was then transformed in a numerical scale in order to allow the comparison with the mathematical measures. It was observed that depending on the parameters used in the restoration algorithm based in Tikhonovs regularization functional and the type of the restored image, the mathematical performance measures based on Bregman distances present better results than those obtained with other usual performance measures such as the Mean Square Error (MSE) yielding to a better agreement with the evaluation performed by the human referees.

Cryo-electron microscopy (cryo-EM) has been established as the leading imaging technique for structural studies from small proteins to whole cells at a molecular level. The great advances in cryo-EM have led to the ability to provide unique insights into a wide variety of biological processes in a close to native, hydrated state at near-atomic resolutions. The developments of computational approaches have significantly contributed to the exciting achievements of cryo-EM. This dissertation emphasizes new approaches to address image processing problems in cryo-EM, including tilt series alignment evaluation, simultaneous determination of sample thickness, tilt, and electron mean free path based on Beer-Lambert law, Model-Based Iterative Reconstruction (MBIR) on tomographic data, minimization of objective lens astigmatism in instrument alignment and defocus and magnification dependent astigmatism of TEM images. The final goal of these methodological developments is to improve the 3D reconstruction of cryo-EM and visualize more detailed characterization.