Sparse Image and Signal Processing: Wavelets, Curvelets, Morphological Diversity - Couverture rigide

Starck, Jean-Luc; Murtagh, Fionn; Fadili, Jalal M.

Couverture rigide

ISBN 10 : 0521119138 ISBN 13 : 9780521119139

Editeur : Cambridge University Press, 2010

Synopsis

Book by Starck JeanLuc Murtagh Fionn Fadili Jalal M

A propos du livre

Revue de presse

'This book is well organized, and it covers the theory and application of multiscale imaging and image processing. The authors provide Matlab algorithms for wavelet, ridgelet and curvelet transformations, as well as numerical experiments with detailed Matlab and IDL code for each chapter. A detailed list of the references provides further exploration of recent publications in the area. The book's contents are well prepared for graduate-level students or advanced undergraduates who work in the field of image and signal processing or computer science. The book is also an indispensable resource for professionals looking to adopt innovative concepts for improving the performance of image processing.' Yan Gao, Optics and Photonics News

'This is an excellent book devoted to an important domain of contemporary science, where the activity includes the following stages: research, theory and publication and the verification of results by the scientific community.' D. Stanomir, Mathematical Reviews

'... effective in delivering a concise overview of the field. The book can be highly useful for researchers and graduate students in engineering and science who are looking for research ideas or are interested in applying the techniques to their application domains ... a welcome addition to the image processing library.' T. Kubota, Computing Reviews

Présentation de l'éditeur

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.

Détails de l'édition

• Éditeur: Cambridge University Press
• Date d'édition: 2010
• ISBN 10: 0521119138
• ISBN 13: 9780521119139
• Reliure: Relié
• Langue: anglais
• Nombre de pages: 336