Sparse image and signal processing : wavelets and related geometric multiscale analysis This thoroughly updated new edition presents state of the art sparse and multiscale image and signal processing. It covers linear multiscale geometric transforms such as wavelet ridgelet or curvelet transforms and non linear multiscale transforms based on the median and mathematical morphology operators. Along with an up to the minute description of required computation it covers the latest results in inverse problem solving and regularization sparse signal decomposition blind source separation in painting and compressed sensing. New chapters and sections cover multiscale geometric transforms for three dimensional data (data cubes) data on the sphere (geo located data) dictionary learning and nonnegative matrix factorization. The authors wed theory and practice in examining applications in areas such as astronomy including recent results from the European Space Agencys Herschel mission biology fusion physics cold dark matter simulation medical MRI digital media and forensics. MATLAB® and IDL code available online at www.SparseSignalRecipes.info accompany these methods and all applications Introduction to the world of sparsity The wavelet transform Redundant wavelet transform Nonlinear multiscale transforms Multiscale geometric transforms Sparsity and noise removal Linear inverse problems Morphological diversity Sparse blind source separation Dictionary learning Three dimensional sparse representations Multiscale geometric analysis on the sphere Compressed sensing This books take home message