A Wavelet Tour of Signal Processing
The Sparse Way

The undisputed reference on wavelet signal processing by the key pioneer in the field - Stéphane Mallat

Stephane Mallat (Author)

9780123743701, Elsevier Science

Hardback, published 18 December 2008

832 pages
23.4 x 19 x 4.1 cm, 1.53 kg

"There is no question that this revision should be published. Mallat’s book is the undisputed reference in this field – it is the only one that covers the essential material in such breadth and depth." --Laurent Demanet, Stanford University

Mallat's book is the undisputed reference in this field - it is the only one that covers the essential material in such breadth and depth. - Laurent Demanet, Stanford University

The new edition of this classic book gives all the major concepts, techniques and applications of sparse representation, reflecting the key role the subject plays in today's signal processing. The book clearly presents the standard representations with Fourier, wavelet and time-frequency transforms, and the construction of orthogonal bases with fast algorithms. The central concept of sparsity is explained and applied to signal compression, noise reduction, and inverse problems, while coverage is given to sparse representations in redundant dictionaries, super-resolution and compressive sensing applications.

Features:

* Balances presentation of the mathematics with applications to signal processing
* Algorithms and numerical examples are implemented in WaveLab, a MATLAB toolbox

New in this edition

* Sparse signal representations in dictionaries
* Compressive sensing, super-resolution and source separation
* Geometric image processing with curvelets and bandlets
* Wavelets for computer graphics with lifting on surfaces
* Time-frequency audio processing and denoising
* Image compression with JPEG-2000
* New and updated exercises

A Wavelet Tour of Signal Processing: The Sparse Way, Third Edition, is an invaluable resource for researchers and R&D engineers wishing to apply the theory in fields such as image processing, video processing and compression, bio-sensing, medical imaging, machine vision and communications engineering.

Stephane Mallat is Professor in Applied Mathematics at École Polytechnique, Paris, France. From 1986 to 1996 he was a Professor at the Courant Institute of Mathematical Sciences at New York University, and between 2001 and 2007, he co-founded and became CEO of an image processing semiconductor company.

PrefaceNotationsSparse RepresentationsFourier KingdomDiscrete RevolutionTime Meets FrequencyFramesWavelet ZoomWavelet BasesWavelet Packet and Local Cosine BasesApproximations in BasesCompressionDenoisingSparse in Redundant DictionariesMathematical Complements

Subject Areas: Signal processing [UYS], Algorithms & data structures [UMB], Communications engineering / telecommunications [TJK], Electricity, electromagnetism & magnetism [PHK]