The new edition of this classic 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 of Fourier, wavelet and time-frequency tools which enable sparse representations of large classes of signals and images, including 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.