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 ÉcolePolytechnique in Paris. New to the Second Edition
(I initiall ready the book in French when I was a master student).
For people interested in getting a strong basis in the foundation of (sparse) signal processing, this is an excellent introduction. This is maybe my favorite "applied math book", that review a lot of the advances in signal processing of late 90ies.
It unfortunately went a bit too early to really cover compressed sensing, though it does cover some related sparse-coding topics.
It can be a fine book for a college class on wavelets. For readers familiar with MATLAB, all the examples in the book can be reproduced with MATLAB "workouts."
It's a great reference, if you take it with a ton of salt: there are way too many typos and subtle mathematical issues to take any result from this book without verification, and once you try to reproduce the plots, you'll realize that there is often not enough information given for you to know exactly how to do so. On the flip side, it covers a range of topics that you wouldn't usually see all in one place.
I have read large portions of this book, but not every page. The book is an excellent example of how a textbook should be written with clear sections on theory, proofs, examples, and questions to solve. If you are bored of FFT and want to discover *why* sin/cos are useful orthogonal functions, then read this book.