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Link de la búsquedaFour Short Courses on Harmonic Analysis / SpringerLink (Online service) ; Brigitte Forster ; Peter Massopust (2010)
Título : Four Short Courses on Harmonic Analysis : Wavelets, Frames, Time-Frequency Methods, and Applications to Signal and Image Analysis Tipo de documento: documento electrónico Autores: SpringerLink (Online service) ; Brigitte Forster ; Peter Massopust Editorial: Boston, MA : Birkhäuser Boston Fecha de publicación: 2010 Colección: Applied and Numerical Harmonic Analysis, ISSN 2296-5009 Número de páginas: XVIII, 249 p. 36 illus Il.: online resource ISBN/ISSN/DL: 978-0-8176-4891-6 Idioma : Inglés (eng) Palabras clave: Mathematics Harmonic analysis Fourier Physics Analysis Abstract Signal, Image and Speech Processing Theoretical, Mathematical Computational Clasificación: 51 Matemáticas Resumen: This state-of-the-art textbook examines four research directions in harmonic analysis and features some of the latest applications in the field, including cosmic microwave background analysis, human cortex image denoising, and wireless communication. The work is the first one that combines spline theory (from a numerical or approximation-theoretical view), wavelets, frames, and time-frequency methods leading up to a construction of wavelets on manifolds other than Rn. Written by internationally renowned mathematicians, the interdisciplinary chapters are expository by design, enabling the reader to understand the theory behind modern image and signal processing methodologies. The main emphasis throughout the book is on the interdependence of the four modern research directions covered. Each chapter ends with exercises that allow for a more in-depth understanding of the material and are intended to stimulate the reader toward further research. A comprehensive index completes the work. Topics covered: * Frames and bases in mathematics and engineering * Wavelets with composite dilations and their applications * Wavelets on the sphere and their applications * Wiener's Lemma: theme and variations Four Short Courses on Harmonic Analysis is intended as a graduate-level textbook for courses or seminars on harmonic analysis and its applications. The work is also an excellent reference or self-study guide for researchers and practitioners with diverse mathematical backgrounds working in different fields such as pure and applied mathematics, image and signal processing engineering, mathematical physics, and communication theory Nota de contenido: Introduction: Mathematical Aspects of Time-Frequency Analysis -- B-Spline Generated Frames -- Continuous and Discrete Reproducing Systems That Arise from Translations. Theory and Applications of Composite Wavelets -- Wavelets on the Sphere -- Wiener’s Lemma: Theme and Variations. An Introduction to Spectral Invariance and Its Applications En línea: http://dx.doi.org/10.1007/978-0-8176-4891-6 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33549 Four Short Courses on Harmonic Analysis : Wavelets, Frames, Time-Frequency Methods, and Applications to Signal and Image Analysis [documento electrónico] / SpringerLink (Online service) ; Brigitte Forster ; Peter Massopust . - Boston, MA : Birkhäuser Boston, 2010 . - XVIII, 249 p. 36 illus : online resource. - (Applied and Numerical Harmonic Analysis, ISSN 2296-5009) .
ISBN : 978-0-8176-4891-6
Idioma : Inglés (eng)
Palabras clave: Mathematics Harmonic analysis Fourier Physics Analysis Abstract Signal, Image and Speech Processing Theoretical, Mathematical Computational Clasificación: 51 Matemáticas Resumen: This state-of-the-art textbook examines four research directions in harmonic analysis and features some of the latest applications in the field, including cosmic microwave background analysis, human cortex image denoising, and wireless communication. The work is the first one that combines spline theory (from a numerical or approximation-theoretical view), wavelets, frames, and time-frequency methods leading up to a construction of wavelets on manifolds other than Rn. Written by internationally renowned mathematicians, the interdisciplinary chapters are expository by design, enabling the reader to understand the theory behind modern image and signal processing methodologies. The main emphasis throughout the book is on the interdependence of the four modern research directions covered. Each chapter ends with exercises that allow for a more in-depth understanding of the material and are intended to stimulate the reader toward further research. A comprehensive index completes the work. Topics covered: * Frames and bases in mathematics and engineering * Wavelets with composite dilations and their applications * Wavelets on the sphere and their applications * Wiener's Lemma: theme and variations Four Short Courses on Harmonic Analysis is intended as a graduate-level textbook for courses or seminars on harmonic analysis and its applications. The work is also an excellent reference or self-study guide for researchers and practitioners with diverse mathematical backgrounds working in different fields such as pure and applied mathematics, image and signal processing engineering, mathematical physics, and communication theory Nota de contenido: Introduction: Mathematical Aspects of Time-Frequency Analysis -- B-Spline Generated Frames -- Continuous and Discrete Reproducing Systems That Arise from Translations. Theory and Applications of Composite Wavelets -- Wavelets on the Sphere -- Wiener’s Lemma: Theme and Variations. An Introduction to Spectral Invariance and Its Applications En línea: http://dx.doi.org/10.1007/978-0-8176-4891-6 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33549 Ejemplares
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Título : From Gestalt Theory to Image Analysis : A Probabilistic Approach Tipo de documento: documento electrónico Autores: Agnés Desolneux ; SpringerLink (Online service) ; Lionel Moisan ; Jean-Michel Morel Editorial: New York, NY : Springer New York Fecha de publicación: 2008 Colección: Interdisciplinary Applied Mathematics, ISSN 0939-6047 num. 34 Número de páginas: XII, 276 p. 130 illus Il.: online resource ISBN/ISSN/DL: 978-0-387-74378-3 Idioma : Inglés (eng) Palabras clave: Computer science Image processing Partial differential equations Applied mathematics Engineering Algorithms Mathematics Visualization Science Processing and Vision Differential Equations Signal, Speech Applications of Clasificación: 51 Matemáticas Resumen: This book introduces the reader to a recent theory in Computer Vision yielding elementary techniques to analyse digital images. These techniques are inspired from and are a mathematical formalization of the Gestalt theory. Gestalt theory, which had never been formalized is a rigorous realm of vision psychology developped between 1923 and 1975. From the mathematical viewpoint the closest field to it is stochastic geometry, involving basic probability and statistics, in the context of image analysis. The book is intended for a multidisciplinary audience of researchers and engineers. It is self contained in three aspects: mathematics, vision and algorithms, and requires only a background of elementary calculus and probability. A large number of illustrations, exercises and examples are included. The authors maintain a public software, MegaWave, containing implementations of most of the image analysis techniques developed in the book Nota de contenido: Gestalt Theory -- The Helmholtz Principle -- Estimating the Binomial Tail -- Alignments in Digital Images -- Maximal Meaningfulness and the Exclusion Principle -- Modes of a Histogram -- Vanishing Points -- Contrasted Boundaries -- Variational or Meaningful Boundaries? -- Clusters -- Binocular Grouping -- A Psychophysical Study of the Helmholtz Principle -- Back to the Gestalt Programme -- Other Theories, Discussion En línea: http://dx.doi.org/10.1007/978-0-387-74378-3 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34191 From Gestalt Theory to Image Analysis : A Probabilistic Approach [documento electrónico] / Agnés Desolneux ; SpringerLink (Online service) ; Lionel Moisan ; Jean-Michel Morel . - New York, NY : Springer New York, 2008 . - XII, 276 p. 130 illus : online resource. - (Interdisciplinary Applied Mathematics, ISSN 0939-6047; 34) .
ISBN : 978-0-387-74378-3
Idioma : Inglés (eng)
Palabras clave: Computer science Image processing Partial differential equations Applied mathematics Engineering Algorithms Mathematics Visualization Science Processing and Vision Differential Equations Signal, Speech Applications of Clasificación: 51 Matemáticas Resumen: This book introduces the reader to a recent theory in Computer Vision yielding elementary techniques to analyse digital images. These techniques are inspired from and are a mathematical formalization of the Gestalt theory. Gestalt theory, which had never been formalized is a rigorous realm of vision psychology developped between 1923 and 1975. From the mathematical viewpoint the closest field to it is stochastic geometry, involving basic probability and statistics, in the context of image analysis. The book is intended for a multidisciplinary audience of researchers and engineers. It is self contained in three aspects: mathematics, vision and algorithms, and requires only a background of elementary calculus and probability. A large number of illustrations, exercises and examples are included. The authors maintain a public software, MegaWave, containing implementations of most of the image analysis techniques developed in the book Nota de contenido: Gestalt Theory -- The Helmholtz Principle -- Estimating the Binomial Tail -- Alignments in Digital Images -- Maximal Meaningfulness and the Exclusion Principle -- Modes of a Histogram -- Vanishing Points -- Contrasted Boundaries -- Variational or Meaningful Boundaries? -- Clusters -- Binocular Grouping -- A Psychophysical Study of the Helmholtz Principle -- Back to the Gestalt Programme -- Other Theories, Discussion En línea: http://dx.doi.org/10.1007/978-0-387-74378-3 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34191 Ejemplares
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Título : Mathematical Image Processing : University of Orléans, France, March 29th - April 1st, 2010 Tipo de documento: documento electrónico Autores: SpringerLink (Online service) ; Maïtine Bergounioux Editorial: Berlin, Heidelberg : Springer Berlin Heidelberg Fecha de publicación: 2011 Colección: Springer Proceedings in Mathematics, ISSN 2190-5614 num. 5 Número de páginas: X, 198 p Il.: online resource ISBN/ISSN/DL: 978-3-642-19604-1 Idioma : Inglés (eng) Palabras clave: Mathematics Image processing Mathematical optimization Optimization Processing and Computer Vision Clasificación: 51 Matemáticas Resumen: The contributions appearing in this volume are a snapshot of the different topics that were discussed during the conference. They mainly concern, image reconstruction, texture extraction and image classification and involve a variety of different methods and applications. Therefore it was impossible to split the papers into generic groups which is why they are presented in alphabetic order. However they mainly concern : texture analysis (5 papers) with different techniques (variational analysis, wavelet and morphological component analysis, fractional Brownian fields), geometrical methods (2 papers ) for restoration and invariant feature detection, classification (with multifractal analysis), neurosciences imaging and analysis of Multi-Valued Images Nota de contenido: Function spaces vs. Scaling Functions: Tools for Image Classification. Stéphane Jaffard, Patrice Abry and Stéphane Roux -- A Second Order Model for 3D-texture Extraction. Maïtine Bergounioux and Minh Phuong Tran -- Analysis of Texture Anisotropy Through Extended Fractional Brownian Fields. Hermine Biermé and Frédéric J.P. Richard -- Image Reconstruction via Hypoelliptic Diffusion on the Bundle of Directions of the Plane. Ugo Boscain, Jean Duplaix, Jean-Paul Gauthier, Francesco Rossi -- Projective Invariant Features Detection and the Registration group. Françoise Dibos -- Morphological Component Analysis for Decomposing Dynamic Textures. Sloven Dubois, Renaud Péteri and Michel Ménard -- Texture Enhancing Based on Variational Image Decomposition. F. Frühauf, C. Pontow, O. Scherzer -- A Locally Anisotropic Model for Image Texture Extraction. Loïc Piffet -- A Neural Field Model for Motion Estimation. Émilien Tlapale, Pierre Kornprobst, Guillaume Masson and Olivier Faugeras -- Non-Local Regularization and Registration of Multi-Valued Images by PDE’s and VariationalMethods on Higher Dimensional Spaces. David Tschumperlé and Luc Brun En línea: http://dx.doi.org/10.1007/978-3-642-19604-1 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33417 Mathematical Image Processing : University of Orléans, France, March 29th - April 1st, 2010 [documento electrónico] / SpringerLink (Online service) ; Maïtine Bergounioux . - Berlin, Heidelberg : Springer Berlin Heidelberg, 2011 . - X, 198 p : online resource. - (Springer Proceedings in Mathematics, ISSN 2190-5614; 5) .
ISBN : 978-3-642-19604-1
Idioma : Inglés (eng)
Palabras clave: Mathematics Image processing Mathematical optimization Optimization Processing and Computer Vision Clasificación: 51 Matemáticas Resumen: The contributions appearing in this volume are a snapshot of the different topics that were discussed during the conference. They mainly concern, image reconstruction, texture extraction and image classification and involve a variety of different methods and applications. Therefore it was impossible to split the papers into generic groups which is why they are presented in alphabetic order. However they mainly concern : texture analysis (5 papers) with different techniques (variational analysis, wavelet and morphological component analysis, fractional Brownian fields), geometrical methods (2 papers ) for restoration and invariant feature detection, classification (with multifractal analysis), neurosciences imaging and analysis of Multi-Valued Images Nota de contenido: Function spaces vs. Scaling Functions: Tools for Image Classification. Stéphane Jaffard, Patrice Abry and Stéphane Roux -- A Second Order Model for 3D-texture Extraction. Maïtine Bergounioux and Minh Phuong Tran -- Analysis of Texture Anisotropy Through Extended Fractional Brownian Fields. Hermine Biermé and Frédéric J.P. Richard -- Image Reconstruction via Hypoelliptic Diffusion on the Bundle of Directions of the Plane. Ugo Boscain, Jean Duplaix, Jean-Paul Gauthier, Francesco Rossi -- Projective Invariant Features Detection and the Registration group. Françoise Dibos -- Morphological Component Analysis for Decomposing Dynamic Textures. Sloven Dubois, Renaud Péteri and Michel Ménard -- Texture Enhancing Based on Variational Image Decomposition. F. Frühauf, C. Pontow, O. Scherzer -- A Locally Anisotropic Model for Image Texture Extraction. Loïc Piffet -- A Neural Field Model for Motion Estimation. Émilien Tlapale, Pierre Kornprobst, Guillaume Masson and Olivier Faugeras -- Non-Local Regularization and Registration of Multi-Valued Images by PDE’s and VariationalMethods on Higher Dimensional Spaces. David Tschumperlé and Luc Brun En línea: http://dx.doi.org/10.1007/978-3-642-19604-1 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33417 Ejemplares
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Título : Mathematical Methods for Signal and Image Analysis and Representation Tipo de documento: documento electrónico Autores: SpringerLink (Online service) ; Luc Florack ; Remco Duits ; Geurt Jongbloed ; Marie-Colette van Lieshout ; Laurie Davies Editorial: London : Springer London Fecha de publicación: 2012 Colección: Computational Imaging and Vision, ISSN 1381-6446 num. 41 Número de páginas: XII, 320 p Il.: online resource ISBN/ISSN/DL: 978-1-4471-2353-8 Idioma : Inglés (eng) Palabras clave: Mathematics Image processing Computer science mathematics Mathematics, general Processing and Vision Mathematical Applications in Science Clasificación: 51 Matemáticas Resumen: Mathematical Methods for Signal and Image Analysis and Representation presents the mathematical methodology for generic image analysis tasks. In the context of this book an image may be any m-dimensional empirical signal living on an n-dimensional smooth manifold (typically, but not necessarily, a subset of spacetime). The existing literature on image methodology is rather scattered and often limited to either a deterministic or a statistical point of view. In contrast, this book brings together these seemingly different points of view in order to stress their conceptual relations and formal analogies. Furthermore, it does not focus on specific applications, although some are detailed for the sake of illustration, but on the methodological frameworks on which such applications are built, making it an ideal companion for those seeking a rigorous methodological basis for specific algorithms as well as for those interested in the fundamental methodology per se. Covering many topics at the forefront of current research, including anisotropic diffusion filtering of tensor fields, this book will be of particular interest to graduate and postgraduate students and researchers in the fields of computer vision, medical imaging and visual perception Nota de contenido: A Short Introduction to Diffusion-like Methods -- Adaptive Filtering using Channel Representations -- 3D-Coherence-Enhancing Diffusion Filtering for Matrix Fields -- Structural Adaptive Smoothing: Principles and Applications in Imaging -- SPD Tensors Regularization via Iwasawa Decomposition -- Sparse Representation of Video Data by Adaptive Tetrahedralizations -- Continuous Diffusion Wavelet Transforms and Scale Space over Euclidean Spaces and Noncommutative Lie Groups -- Left Invariant Evolution Equations on Gabor Transforms -- Scale Space Representations Locally Adapted to the Geometry of Base and Target Manifold -- An A Priori Model of Line Propagation -- Local Statistics on Shape Diffeomorphisms using a Depth Potential Function -- Preserving Time Structures while Denoising a Dynamical Image -- Interacting Adaptive Filters for Multiple Objects Detection -- Visual Data Recognition and Modeling based on Local Markovian Models -- Locally Specified Polygonal Markov Fields for Image Segmentation -- Regularization with Approximated L2 Maximum Entropy Method. En línea: http://dx.doi.org/10.1007/978-1-4471-2353-8 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=32719 Mathematical Methods for Signal and Image Analysis and Representation [documento electrónico] / SpringerLink (Online service) ; Luc Florack ; Remco Duits ; Geurt Jongbloed ; Marie-Colette van Lieshout ; Laurie Davies . - London : Springer London, 2012 . - XII, 320 p : online resource. - (Computational Imaging and Vision, ISSN 1381-6446; 41) .
ISBN : 978-1-4471-2353-8
Idioma : Inglés (eng)
Palabras clave: Mathematics Image processing Computer science mathematics Mathematics, general Processing and Vision Mathematical Applications in Science Clasificación: 51 Matemáticas Resumen: Mathematical Methods for Signal and Image Analysis and Representation presents the mathematical methodology for generic image analysis tasks. In the context of this book an image may be any m-dimensional empirical signal living on an n-dimensional smooth manifold (typically, but not necessarily, a subset of spacetime). The existing literature on image methodology is rather scattered and often limited to either a deterministic or a statistical point of view. In contrast, this book brings together these seemingly different points of view in order to stress their conceptual relations and formal analogies. Furthermore, it does not focus on specific applications, although some are detailed for the sake of illustration, but on the methodological frameworks on which such applications are built, making it an ideal companion for those seeking a rigorous methodological basis for specific algorithms as well as for those interested in the fundamental methodology per se. Covering many topics at the forefront of current research, including anisotropic diffusion filtering of tensor fields, this book will be of particular interest to graduate and postgraduate students and researchers in the fields of computer vision, medical imaging and visual perception Nota de contenido: A Short Introduction to Diffusion-like Methods -- Adaptive Filtering using Channel Representations -- 3D-Coherence-Enhancing Diffusion Filtering for Matrix Fields -- Structural Adaptive Smoothing: Principles and Applications in Imaging -- SPD Tensors Regularization via Iwasawa Decomposition -- Sparse Representation of Video Data by Adaptive Tetrahedralizations -- Continuous Diffusion Wavelet Transforms and Scale Space over Euclidean Spaces and Noncommutative Lie Groups -- Left Invariant Evolution Equations on Gabor Transforms -- Scale Space Representations Locally Adapted to the Geometry of Base and Target Manifold -- An A Priori Model of Line Propagation -- Local Statistics on Shape Diffeomorphisms using a Depth Potential Function -- Preserving Time Structures while Denoising a Dynamical Image -- Interacting Adaptive Filters for Multiple Objects Detection -- Visual Data Recognition and Modeling based on Local Markovian Models -- Locally Specified Polygonal Markov Fields for Image Segmentation -- Regularization with Approximated L2 Maximum Entropy Method. En línea: http://dx.doi.org/10.1007/978-1-4471-2353-8 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=32719 Ejemplares
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Título : Mathematical Problems in Image Processing : Partial Differential Equations and the Calculus of Variations Tipo de documento: documento electrónico Autores: Gilles Aubert ; SpringerLink (Online service) ; Pierre Kornprobst Editorial: New York, NY : Springer New York Fecha de publicación: 2006 Colección: Applied Mathematical Sciences, ISSN 0066-5452 num. 147 Número de páginas: XXXI, 379 p Il.: online resource ISBN/ISSN/DL: 978-0-387-44588-5 Idioma : Inglés (eng) Palabras clave: Mathematics Image processing Mathematical analysis Analysis (Mathematics) Partial differential equations Optics Optoelectronics Plasmons (Physics) Applied mathematics Engineering Optics, Optoelectronics, Plasmonics and Optical Devices Appl.Mathematics/Computational Methods of Differential Equations Processing Computer Vision Signal, Speech Clasificación: 51 Matemáticas Resumen: Partial differential equations (PDEs) and variational methods were introduced into image processing about fifteen years ago. Since then, intensive research has been carried out. The goals of this book are to present a variety of image analysis applications, the precise mathematics involved and how to discretize them. Thus, this book is intended for two audiences. The first is the mathematical community by showing the contribution of mathematics to this domain. It is also the occasion to highlight some unsolved theoretical questions. The second is the computer vision community by presenting a clear, self-contained and global overview of the mathematics involved in image processing problems. This work will serve as a useful source of reference and inspiration for fellow researchers in Applied Mathematics and Computer Vision, as well as being a basis for advanced courses within these fields. During the four years since the publication of the first edition, there has been substantial progress in the range of image processing applications covered by the PDE framework. The main goals of the second edition are to update the first edition by giving a coherent account of some of the recent challenging applications, and to update the existing material. In addition, this book provides the reader with the opportunity to make his own simulations with a minimal effort. To this end, programming tools are made available, which will allow the reader to implement and test easily some classical approaches. Reviews of the earlier edition: "Mathematical Problems in Image Processing is a major, elegant, and unique contribution to the applied mathematics literature, oriented toward applications in image processing and computer vision.... Researchers and practitioners working in the field will benefit by adding this book to their personal collection. Students and instructors will benefit by using this book as a graduate course textbook." -- SIAM Review "The Mathematician -- and he doesn't need to be a 'die-hard' applied mathematician -- will love it because there are all these spectacular applications of nontrivial mathematical techniques and he can even find some open theoretical questions. The numerical analyst will discover many challenging problems and implementations. The image processor will be an eager reader because the book provides all the mathematical elements, including most of the proofs.... Both content and typography are a delight. I can recommend the book warmly for theoretical and applied researchers." -- Bulletin of the Belgian Mathematics Nota de contenido: Foreword -- Preface to the Second Edition -- Preface -- Guide to the Main Mathematical Concepts and their Application -- Notation and Symbols -- Introduction -- Mathematical Preliminaries -- Image Restoration -- The Segmentation Problem -- Other Challenging Applications -- A Introduction to Finite Difference Methods -- B Experiment Yourself!- References -- Index En línea: http://dx.doi.org/10.1007/978-0-387-44588-5 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34844 Mathematical Problems in Image Processing : Partial Differential Equations and the Calculus of Variations [documento electrónico] / Gilles Aubert ; SpringerLink (Online service) ; Pierre Kornprobst . - New York, NY : Springer New York, 2006 . - XXXI, 379 p : online resource. - (Applied Mathematical Sciences, ISSN 0066-5452; 147) .
ISBN : 978-0-387-44588-5
Idioma : Inglés (eng)
Palabras clave: Mathematics Image processing Mathematical analysis Analysis (Mathematics) Partial differential equations Optics Optoelectronics Plasmons (Physics) Applied mathematics Engineering Optics, Optoelectronics, Plasmonics and Optical Devices Appl.Mathematics/Computational Methods of Differential Equations Processing Computer Vision Signal, Speech Clasificación: 51 Matemáticas Resumen: Partial differential equations (PDEs) and variational methods were introduced into image processing about fifteen years ago. Since then, intensive research has been carried out. The goals of this book are to present a variety of image analysis applications, the precise mathematics involved and how to discretize them. Thus, this book is intended for two audiences. The first is the mathematical community by showing the contribution of mathematics to this domain. It is also the occasion to highlight some unsolved theoretical questions. The second is the computer vision community by presenting a clear, self-contained and global overview of the mathematics involved in image processing problems. This work will serve as a useful source of reference and inspiration for fellow researchers in Applied Mathematics and Computer Vision, as well as being a basis for advanced courses within these fields. During the four years since the publication of the first edition, there has been substantial progress in the range of image processing applications covered by the PDE framework. The main goals of the second edition are to update the first edition by giving a coherent account of some of the recent challenging applications, and to update the existing material. In addition, this book provides the reader with the opportunity to make his own simulations with a minimal effort. To this end, programming tools are made available, which will allow the reader to implement and test easily some classical approaches. Reviews of the earlier edition: "Mathematical Problems in Image Processing is a major, elegant, and unique contribution to the applied mathematics literature, oriented toward applications in image processing and computer vision.... Researchers and practitioners working in the field will benefit by adding this book to their personal collection. Students and instructors will benefit by using this book as a graduate course textbook." -- SIAM Review "The Mathematician -- and he doesn't need to be a 'die-hard' applied mathematician -- will love it because there are all these spectacular applications of nontrivial mathematical techniques and he can even find some open theoretical questions. The numerical analyst will discover many challenging problems and implementations. The image processor will be an eager reader because the book provides all the mathematical elements, including most of the proofs.... Both content and typography are a delight. I can recommend the book warmly for theoretical and applied researchers." -- Bulletin of the Belgian Mathematics Nota de contenido: Foreword -- Preface to the Second Edition -- Preface -- Guide to the Main Mathematical Concepts and their Application -- Notation and Symbols -- Introduction -- Mathematical Preliminaries -- Image Restoration -- The Segmentation Problem -- Other Challenging Applications -- A Introduction to Finite Difference Methods -- B Experiment Yourself!- References -- Index En línea: http://dx.doi.org/10.1007/978-0-387-44588-5 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34844 Ejemplares
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