
Sparse Image and Signal Processing
Wavelets, Curvelets, Morphological Diversity
Cambridge University Press
Published on 10. May 2010
Book
Hardback
336 pages
978-0-521-11913-9 (ISBN)
Article exhausted; check for reprint
Description
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.
Reviews / Votes
'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 ReviewsMore details
Language
English
Place of publication
Cambridge
United Kingdom
Target group
Professional and scholarly
Illustrations
6 Tables, unspecified; 27 Plates, unspecified; 56 Halftones, unspecified; 54 Line drawings, unspecified
Dimensions
Height: 261 mm
Width: 183 mm
Thickness: 24 mm
Weight
770 gr
ISBN-13
978-0-521-11913-9 (9780521119139)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
New editions

Jean-Luc Starck | Fionn Murtagh | Jalal Fadili
Sparse Image and Signal Processing
Wavelets and Related Geometric Multiscale Analysis, Second Edition
Book
10/2015
2nd Edition
Cambridge University Press
€136.40
Shipment within 15-20 days
Additional editions

Jean-Luc Starck | Fionn Murtagh | Jalal M. Fadili
Sparse Image and Signal Processing
Wavelets, Curvelets, Morphological Diversity
E-Book
05/2010
1st Edition
Cambridge University Press
€64.99
Available for download

E-Book
05/2010
Cambridge University Press
€53.99
Available for download
Persons
Jean-Luc Starck is a researcher at the Institute of Research into the Fundamental Laws of the Universe (IRFU), CEA-Saclay. He holds a Ph.D. from the University of Nice-Sophia Antipolis and Observatory of Cote d'Azur and a habilitation degree from the University Paris XI. He is a former visiting researcher at the European Southern Observatory (ESO), UCLA, and the Statistics Department at Stanford University. His research interests include image processing, statistical methods in astrophysics, and cosmology. He is also author of two books, entitled Image Processing and Data Analysis: The Multiscale Approach and Astronomical Image and Data Analysis. Fionn Murtagh directs Ireland's Science Foundation funding programs in Information and Communications Technologies and Energy. He holds a Ph.D. from the Universite Paris 6 and a habilitation from Universite de Strasbourg. Murtagh held professorial chairs at the University of Ulster, Queen's University Belfast, and now at Royal Holloway, University of London. He is a Fellow of the International Association for Pattern Recognition, a Fellow of the British Computer Society, and an elected Member of the Royal Irish Academy. Jalal M. Fadili graduated from the Ecole Nationale Superieure d'Ingenieurs (ENSI) de Caen, France, and received MSc and Ph.D. degrees in signal and image processing from the University of Caen. He was a Research Associate with the University of Cambridge (McDonnell-Pew Fellow) from 1999 to 2000. He has been an Associate Professor of signal and image processing since September 2001 at ENSI. He was a visitor at several universities (QUT-Australia, Stanford University, CalTech, EPFL). His research interests include mathematical signal and image processing, statistics, optimization theory, and sparse representations.
Author
Royal Holloway, University of London
Ecole Nationale Superieure d'Ingenieurs de Caen, France
Content
1. Introduction to the world of sparsity; 2. The wavelet transform; 3. Redundant wavelet transform; 4. Nonlinear multiscale transforms; 5. The ridgelet and curvelet transforms; 6. Sparsity and noise removal; 7. Linear inverse problems; 8. Morphological diversity; 9. Sparse blind source separation; 10. Multiscale geometric analysis on the sphere; 11. Compressed sensing.