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236862Sparse and Redundant Representations and THeir Applications in Signal and Image Processing
Semester:
Winter 2013/4
Description:

A graduate course on sparse representations and their uses in signal and image processing. The course covers theoretical aspects of this field (e.g. uniqueness of sparse representation, pursuit performance), practical issues (e.g. dictionary learning, efficient numerical schemes for pursuit), and applications in image processing (denoising, inpainting, deblurring, compression).