Documents disponibles écrits par cet auteur

Image Processing and Analysis / Tony F. Chan

Public ISBD Titre : Image Processing and Analysis : variational, PDE, wavelet, and stochastic methods Type de document : texte imprimé Auteurs : Tony F. Chan, Auteur ; Jianhong (Jackie) Shen, Auteur Editeur : Philadelphia : SIAM Année de publication : 2005 Importance : 400 p. Présentation : couv. ill.,ill. Format : 25,2 cm. ISBN/ISSN/EAN : 978-0-89871-589-7 Langues : Anglais (eng) Catégories : AUTOMATISME Index. décimale : 25-05 Application du traitement numérique du signal Résumé : At no other time in human history have the influence and impact of image processing on modern society, science, and technology been so explosive. Image processing has become a critical component in contemporary science and technology and has many important applications. This book develops the mathematical foundation of modern image processing and low-level computer vision, and presents a general framework from the analysis of image structures and patterns to their processing. The core mathematical and computational ingredients of several important image processing tasks are investigated. The book bridges contemporary mathematics with state-of-the-art methodologies in modern image processing while organizing the vast contemporary literature into a coherent and logical structure. Image processing has traditionally been built on the machinery of Fourier and spectral analysis; however, in the past few decades numerous novel competing methods and tools have emerged. These diversified approaches, although seemingly distinct, are in fact intrinsically connected. The authors integrate this diversity of modern image processing approaches by revealing the few common threads connecting them. Some newer emergent integration efforts have also been highlighted and analyzed. Image Processing and Analysis: Variational, PDE, Wavelet, and Stochastic Methods is systematic and well organized. The authors first investigate the geometric, functional, and atomic structures of images and then rigorously develop and analyze several image processors. The book is comprehensive and integrative, covering the four most powerful classes of mathematical tools in contemporary image analysis and processing while exploring their intrinsic connections and integration. The material is balanced in theory and computation, following a solid theoretical analysis of model building and performance with computational implementation and numerical examples. Note de contenu : Sommaire 1 Introduction 2 Some Modern Image Analysis Tools 3 Image Modeling and Representation 4 Image Denoising 5 Image Deblurring 6 Image Inpainting 7 Image Segmentation -Index Image Processing and Analysis : variational, PDE, wavelet, and stochastic methods [texte imprimé] / Tony F. Chan, Auteur ; Jianhong (Jackie) Shen, Auteur . - Philadelphia : SIAM, 2005 . - 400 p. : couv. ill.,ill. ; 25,2 cm. ISBN : 978-0-89871-589-7 Langues : Anglais (eng) Catégories : AUTOMATISME Index. décimale : 25-05 Application du traitement numérique du signal Résumé : At no other time in human history have the influence and impact of image processing on modern society, science, and technology been so explosive. Image processing has become a critical component in contemporary science and technology and has many important applications. This book develops the mathematical foundation of modern image processing and low-level computer vision, and presents a general framework from the analysis of image structures and patterns to their processing. The core mathematical and computational ingredients of several important image processing tasks are investigated. The book bridges contemporary mathematics with state-of-the-art methodologies in modern image processing while organizing the vast contemporary literature into a coherent and logical structure. Image processing has traditionally been built on the machinery of Fourier and spectral analysis; however, in the past few decades numerous novel competing methods and tools have emerged. These diversified approaches, although seemingly distinct, are in fact intrinsically connected. The authors integrate this diversity of modern image processing approaches by revealing the few common threads connecting them. Some newer emergent integration efforts have also been highlighted and analyzed. Image Processing and Analysis: Variational, PDE, Wavelet, and Stochastic Methods is systematic and well organized. The authors first investigate the geometric, functional, and atomic structures of images and then rigorously develop and analyze several image processors. The book is comprehensive and integrative, covering the four most powerful classes of mathematical tools in contemporary image analysis and processing while exploring their intrinsic connections and integration. The material is balanced in theory and computation, following a solid theoretical analysis of model building and performance with computational implementation and numerical examples. Note de contenu : Sommaire 1 Introduction 2 Some Modern Image Analysis Tools 3 Image Modeling and Representation 4 Image Denoising 5 Image Deblurring 6 Image Inpainting 7 Image Segmentation -Index

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Image Processing Based on Partial Differential Equations / Xue-Cheng Tai

Public ISBD Titre : Image Processing Based on Partial Differential Equations : proceedings of the International Conference on PDE-Based Image Processing and Related Inverse Problems, CMA, Oslo, August 8-12, 2005 Type de document : texte imprimé Auteurs : Xue-Cheng Tai, Auteur ; Knut-Andreas Lie, Auteur ; Tony F. Chan, Auteur Editeur : Berlin Heidelberg : Springer-Verlag Année de publication : 2007 Collection : Mathematics and Visualization Importance : 440 p. Présentation : couv. ill. en coul., ill. Format : 24 cm. ISBN/ISSN/EAN : 978-3-540-33266-4 Langues : Anglais (eng) Catégories : AUTOMATISME Mots-clés : 3D  Alignment  Analysis  Diffusion  Interpolation  Moment  image processing  image registration  signal processing  simulation visualization Index. décimale : 25-05 Application du traitement numérique du signal Résumé : This book publishes a collection of original scientific research articles that address the state-of-art in using partial differential equations for image and signal processing. Coverage includes: level set methods for image segmentation and construction, denoising techniques, digital image inpainting, image dejittering, image registration, and fast numerical algorithms for solving these problems. The book is suitable for readers working with computer vision and visualization, image and signal processing, as well as medical imaging and numerical mathematics. The partial differential equations used for different problems discussed in this proceeding provide some rich research topics for people working with mathematical analysis and numerical simulations. This volume collects new developments in this field and points to the newest literature results. It is good resource for people working on related problems as well as for people who are new in this field. Note de contenu : Contents Part I Digital Image Inpainting, Image Dejittering, and Optical Flow Estimation -Image Inpainting Using a TV-Stokes Equation -Error Analysis for H1 Based Wavelet Interpolations -Image Dejittering Based on Slicing Moments -CLG Method for Optical Flow Estimation Based on Gradient Constancy Assumption Part II Denoising and Total Variation Methods -On Multigrids for Solving a Class of Improved Total Variation Based Staircasing Reduction Models -A Method for Total Variation-based Reconstruction of Noisy and Blurred Images -Minimization of an Edge-Preserving Regularization Functional by Conjugate Gradient Type Methods -A Newton-type Total Variation Diminishing Flow -Chromaticity Denoising using Solution to the Skorokhod Problem -Improved 3D Reconstruction of Interphase Chromosomes Based on Nonlinear Diffusion Filtering Part III Image Segmentation -Some Recent Developments in Variational Image Segmentation -Application of Non-Convex BV Regularization for Image Segmentation -Region-Based Variational Problems and Normal Alignment -Geometric Interpretation of Descent PDEs -Fast PCLSM with Newton Updating Algorithm Part IV Fast Numerical Methods -Nonlinear Multilevel Schemes for Solving the Total Variation Image Minimization Problem -Fast Implementation of Piecewise Constant Level Set Methods -The Multigrid Image Transform -Minimally Stochastic Schemes for Singular Diffusion Equations Part V Image Registration -Total Variation Based Image Registration -Variational Image Registration Allowing for Discontinuities in the Displacement Field Part IV Inverse Problems -Shape Reconstruction from Two-Phase Incompressible Flow Data using Level Sets -Reservoir Description Using a Binary Level Set Approach with Additional Prior Information About the Reservoir Model Image Processing Based on Partial Differential Equations : proceedings of the International Conference on PDE-Based Image Processing and Related Inverse Problems, CMA, Oslo, August 8-12, 2005 [texte imprimé] / Xue-Cheng Tai, Auteur ; Knut-Andreas Lie, Auteur ; Tony F. Chan, Auteur . - Berlin Heidelberg : Springer-Verlag, 2007 . - 440 p. : couv. ill. en coul., ill. ; 24 cm.. - (Mathematics and Visualization) . ISBN : 978-3-540-33266-4 Langues : Anglais (eng) Catégories : AUTOMATISME Mots-clés : 3D  Alignment  Analysis  Diffusion  Interpolation  Moment  image processing  image registration  signal processing  simulation visualization Index. décimale : 25-05 Application du traitement numérique du signal Résumé : This book publishes a collection of original scientific research articles that address the state-of-art in using partial differential equations for image and signal processing. Coverage includes: level set methods for image segmentation and construction, denoising techniques, digital image inpainting, image dejittering, image registration, and fast numerical algorithms for solving these problems. The book is suitable for readers working with computer vision and visualization, image and signal processing, as well as medical imaging and numerical mathematics. The partial differential equations used for different problems discussed in this proceeding provide some rich research topics for people working with mathematical analysis and numerical simulations. This volume collects new developments in this field and points to the newest literature results. It is good resource for people working on related problems as well as for people who are new in this field. Note de contenu : Contents Part I Digital Image Inpainting, Image Dejittering, and Optical Flow Estimation -Image Inpainting Using a TV-Stokes Equation -Error Analysis for H1 Based Wavelet Interpolations -Image Dejittering Based on Slicing Moments -CLG Method for Optical Flow Estimation Based on Gradient Constancy Assumption Part II Denoising and Total Variation Methods -On Multigrids for Solving a Class of Improved Total Variation Based Staircasing Reduction Models -A Method for Total Variation-based Reconstruction of Noisy and Blurred Images -Minimization of an Edge-Preserving Regularization Functional by Conjugate Gradient Type Methods -A Newton-type Total Variation Diminishing Flow -Chromaticity Denoising using Solution to the Skorokhod Problem -Improved 3D Reconstruction of Interphase Chromosomes Based on Nonlinear Diffusion Filtering Part III Image Segmentation -Some Recent Developments in Variational Image Segmentation -Application of Non-Convex BV Regularization for Image Segmentation -Region-Based Variational Problems and Normal Alignment -Geometric Interpretation of Descent PDEs -Fast PCLSM with Newton Updating Algorithm Part IV Fast Numerical Methods -Nonlinear Multilevel Schemes for Solving the Total Variation Image Minimization Problem -Fast Implementation of Piecewise Constant Level Set Methods -The Multigrid Image Transform -Minimally Stochastic Schemes for Singular Diffusion Equations Part V Image Registration -Total Variation Based Image Registration -Variational Image Registration Allowing for Discontinuities in the Displacement Field Part IV Inverse Problems -Shape Reconstruction from Two-Phase Incompressible Flow Data using Level Sets -Reservoir Description Using a Binary Level Set Approach with Additional Prior Information About the Reservoir Model

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Code-barres	Cote	Support	Localisation	Section	Disponibilité	N.Inventaire
1617	25-05-41	Livre	Bibliothèque de Génie Electrique- USTO	Documentaires	Exclu du prêt	1617