商品簡介
"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 available for download at the associated Web site"--Provided by publisher.
作者簡介
Jean-LucStarck is Senior Scientist at the Fundamental Laws of the Universe Research Institute, CEA-Saclay. He holds a PhD from the University of Nice Sophia Antipolis and the Observatory of the Cote d'Azur, and a Habilitation degree from the University Paris 11. He has held visiting appointments at the European Southern Observatory, the University of California Los Angeles, and the Statistics Department, Stanford University. He is author of the following books: Image Pro-cessing and Data Analysis: The Multiscale Approach and Astronomical Image and Data Analysis. In 2009, he won a European Research Council Advanced Investigator award.
Fionn Murtagh directs Science Foundation Ireland's national funding programs in Information and Communications Technologies, and in Energy. He holds a PhD in Mathematical Statistics from the University of Paris 6, and a Habilitation from the University of Strasbourg. He has held professorial chairs in computer science at the University of Ulster, Queen's University Belfast, and now in the University of London at Royal Holloway. He is a Member of the Royal Irish Academy, a Fellow of the International Association for Pattern Recognition, and a Fellow of the British Computer Society.
Jalal M. Fadili graduated from the Ecole Nationale Superieured'lngenieurs (ENSI), Caen, France and received MSc and PhD degrees in signal processing, and a Habilitation, from the University of Caen. He was McDonnell-Pew Fellow at the University of Cambridge in 1999-2000. Since 2001 he is Associate Professor of Signal and Image Processing at ENSI. He has held visiting appointments at Queensland University of Technology, Stanford University, Caltech, and EPFL.
