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Showing 1 to 3 of 3 for “"Sparsifying transform learning"”.
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Adaptive nonlocal and structured sparse signal modeling and applications
… signal modeling. However, synthesis dictionary learning typically involves expensive sparse coding and learning steps. Recently, sparsifying transform learning received interest for its cheap computation and its optimal updates in the alternating algorithms. Prior works on transform learning …
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Transform learning based image and video processing
… from a good adaptive sparse model. Recently, the sparsifying transform model has received interest, for which sparse coding is cheap and exact, and learning, or data-driven adaptation admits computationally efficient solutions. In this thesis, we present two extensions to the transform learning …
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Adaptive sparse representations and their applications
"The sparsity of signals and images in a certain transform domain or dictionary has been exploited in many applications in signal processing, image processing, and medical imaging. Analytical sparsifying transforms such as Wavelets and DCT have been widely used in compression standards. Recently, …