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. Companion website for instructors and selected solutions and code available for students. 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.