Sparsity Based Methods for Overparameterized Variational Problems
DOI10.1137/140998585zbMath1328.47080arXiv1405.4969OpenAlexW2962781485MaRDI QIDQ3454487
Raja Giryes, Michael Elad, Alfred Marcel Bruckstein
Publication date: 25 November 2015
Published in: SIAM Journal on Imaging Sciences (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1405.4969
total variationvariational methodsdenoisingimage segmentationsparsitycompressed sensingoverparameterizationcosparsityline segmentation
Computing methodologies for image processing (68U10) Variational methods applied to PDEs (35A15) Numerical aspects of computer graphics, image analysis, and computational geometry (65D18) Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Method of lines for initial value and initial-boundary value problems involving PDEs (65M20) Applications of operator theory in optimization, convex analysis, mathematical programming, economics (47N10) Inverse problems in optimal control (49N45) Numerical solution to inverse problems in abstract spaces (65J22)
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