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Sparse Image And Signal Processing

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Sparse Image And Signal Processing

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Author : Jean-Luc Starck
language : en
Publisher: Cambridge University Press
Release Date : 2010-05-10

Sparse Image And Signal Processing written by Jean-Luc Starck and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-05-10 with Computers categories.

This book presents the state of the art in sparse and multiscale image and signal processing, covering linear multiscale transforms, such as wavelet, ridgelet, or curvelet transforms, and non-linear multiscale transforms based on the median and mathematical morphology operators. Recent concepts of sparsity and morphological diversity are described and exploited for various problems such as denoising, inverse problem regularization, sparse signal decomposition, blind source separation, and compressed sensing. This book weds theory and practice in examining applications in areas such as astronomy, biology, physics, digital media, and forensics. A final chapter explores a paradigm shift in signal processing, showing that previous limits to information sampling and extraction can be overcome in very significant ways. Matlab and IDL code accompany these methods and applications to reproduce the experiments and illustrate the reasoning and methodology of the research are available for download at the associated web site.

Sparse Image And Signal Processing

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Author : Jean-Luc Starck
language : en
Publisher: Cambridge University Press
Release Date : 2015-10-14

Presents state-of-the-art sparse and multiscale image and signal processing with applications in astronomy, biology, MRI, media, and forensics.

Sparse Image And Signal Processing

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Author : Jean-Luc Starck
language : en
Publisher: Cambridge University Press
Release Date : 2010-05-10

Sparse Image And Signal Processing Second Edition

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Author : Jean-Luc Starck. Fionn Murtagh. Jalal Fadili
language : en
Publisher:
Release Date : 2015

Sparse Image And Signal Processing Second Edition written by Jean-Luc Starck. Fionn Murtagh. Jalal Fadili and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.

Sparse Image And Signal Processing Second Edition

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Author : Jean-Luc Starck
language : en
Publisher:
Release Date : 2015

Sparse Image And Signal Processing Second Edition written by Jean-Luc Starck and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.

This thoroughly updated new edition presents state of the art sparse and multiscale image and signal processing. It covers linear multiscale geometric transforms, such as wavelet, ridgelet, or curvelet transforms, and non-linear multiscale transforms based on the median and mathematical morphology operators. Along with an up-to-the-minute description of required computation, it covers the latest results in inverse problem solving and regularization, sparse signal decomposition, blind source separation, in-painting, and compressed sensing. New chapters and sections cover multiscale geometric transforms for three-dimensional data (data cubes), data on the sphere (geo-located data), dictionary learning, and nonnegative matrix factorization. The authors wed theory and practice in examining applications in areas such as astronomy, including recent results from the European Space Agency's Herschel mission, biology, fusion physics, cold dark matter simulation, medical MRI, digital media, and forensics. MATLAB® and IDL code, available online at www.SparseSignalRecipes.info, accompany these methods and all applications.

Sparse And Redundant Representations

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Author : Michael Elad
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-08-12

Sparse And Redundant Representations written by Michael Elad and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-08-12 with Mathematics categories.

A long long time ago, echoing philosophical and aesthetic principles that existed since antiquity, William of Ockham enounced the principle of parsimony, better known today as Ockham’s razor: “Entities should not be multiplied without neces sity. ” This principle enabled scientists to select the ”best” physical laws and theories to explain the workings of the Universe and continued to guide scienti?c research, leadingtobeautifulresultsliketheminimaldescriptionlength approachtostatistical inference and the related Kolmogorov complexity approach to pattern recognition. However, notions of complexity and description length are subjective concepts anddependonthelanguage“spoken”whenpresentingideasandresults. The?eldof sparse representations, that recently underwent a Big Bang like expansion, explic itly deals with the Yin Yang interplay between the parsimony of descriptions and the “language” or “dictionary” used in them, and it became an extremely exciting area of investigation. It already yielded a rich crop of mathematically pleasing, deep and beautiful results that quickly translated into a wealth of practical engineering applications. You are holding in your hands the ?rst guide book to Sparseland, and I am sure you’ll ?nd in it both familiar and new landscapes to see and admire, as well as ex cellent pointers that will help you ?nd further valuable treasures. Enjoy the journey to Sparseland! Haifa, Israel, December 2009 Alfred M. Bruckstein vii Preface This book was originally written to serve as the material for an advanced one semester (fourteen 2 hour lectures) graduate course for engineering students at the Technion, Israel.

Sparse Approximations In Signal And Image Processing

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Author :
language : en
Publisher:
Release Date : 2006

Sparse Approximations In Signal And Image Processing written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with categories.

Image Understanding Using Sparse Representations

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Author : Jayaraman J. Thiagarajan
language : en
Publisher: Springer Nature
Release Date : 2022-06-01

Image Understanding Using Sparse Representations written by Jayaraman J. Thiagarajan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Technology & Engineering categories.

Image understanding has been playing an increasingly crucial role in several inverse problems and computer vision. Sparse models form an important component in image understanding, since they emulate the activity of neural receptors in the primary visual cortex of the human brain. Sparse methods have been utilized in several learning problems because of their ability to provide parsimonious, interpretable, and efficient models. Exploiting the sparsity of natural signals has led to advances in several application areas including image compression, denoising, inpainting, compressed sensing, blind source separation, super-resolution, and classification. The primary goal of this book is to present the theory and algorithmic considerations in using sparse models for image understanding and computer vision applications. To this end, algorithms for obtaining sparse representations and their performance guarantees are discussed in the initial chapters. Furthermore, approaches for designing overcomplete, data-adapted dictionaries to model natural images are described. The development of theory behind dictionary learning involves exploring its connection to unsupervised clustering and analyzing its generalization characteristics using principles from statistical learning theory. An exciting application area that has benefited extensively from the theory of sparse representations is compressed sensing of image and video data. Theory and algorithms pertinent to measurement design, recovery, and model-based compressed sensing are presented. The paradigm of sparse models, when suitably integrated with powerful machine learning frameworks, can lead to advances in computer vision applications such as object recognition, clustering, segmentation, and activity recognition. Frameworks that enhance the performance of sparse models in such applications by imposing constraints based on the prior discriminatory information and the underlying geometrical structure, and kernelizing the sparse coding and dictionary learning methods are presented. In addition to presenting theoretical fundamentals in sparse learning, this book provides a platform for interested readers to explore the vastly growing application domains of sparse representations.

A Wavelet Tour Of Signal Processing

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Author : Stephane Mallat
language : en
Publisher: Elsevier
Release Date : 1999-09-14

A Wavelet Tour Of Signal Processing written by Stephane Mallat and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-09-14 with Mathematics categories.

This book is intended to serve as an invaluable reference for anyone concerned with the application of wavelets to signal processing. It has evolved from material used to teach "wavelet signal processing" courses in electrical engineering departments at Massachusetts Institute of Technology and Tel Aviv University, as well as applied mathematics departments at the Courant Institute of New York University and École Polytechnique in Paris. Provides a broad perspective on the principles and applications of transient signal processing with wavelets Emphasizes intuitive understanding, while providing the mathematical foundations and description of fast algorithms Numerous examples of real applications to noise removal, deconvolution, audio and image compression, singularity and edge detection, multifractal analysis, and time-varying frequency measurements Algorithms and numerical examples are implemented in Wavelab, which is a Matlab toolbox freely available over the Internet Content is accessible on several level of complexity, depending on the individual reader's needs New to the Second Edition Optical flow calculation and video compression algorithms Image models with bounded variation functions Bayes and Minimax theories for signal estimation 200 pages rewritten and most illustrations redrawn More problems and topics for a graduate course in wavelet signal processing, in engineering and applied mathematics

Sparse Modeling For Image And Vision Processing

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Author : Julien Mairal
language : en
Publisher: Now Publishers
Release Date : 2014-12-19

Sparse Modeling For Image And Vision Processing written by Julien Mairal and has been published by Now Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-19 with Computers categories.

Sparse Modeling for Image and Vision Processing offers a self-contained view of sparse modeling for visual recognition and image processing. More specifically, it focuses on applications where the dictionary is learned and adapted to data, yielding a compact representation that has been successful in various contexts.

Sparse Image And Signal Processing

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