Learning Consistent Discretizations of the Total Variation
DOI10.1137/20M1377199zbMath1477.49047OpenAlexW3167249630MaRDI QIDQ5860342
Antonin Chambolle, Thomas Pock
Publication date: 19 November 2021
Published in: SIAM Journal on Imaging Sciences (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1137/20m1377199
discretizationtotal variationfinite elementslearningfinite differencesimage denoisingbilevel optimizationimage inpaintingprimal-dual algorithms
Finite element, Rayleigh-Ritz and Galerkin methods for boundary value problems involving PDEs (65N30) Numerical aspects of computer graphics, image analysis, and computational geometry (65D18) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Mesh generation, refinement, and adaptive methods for boundary value problems involving PDEs (65N50) Free boundary problems for PDEs (35R35) Finite difference methods for boundary value problems involving PDEs (65N06) Discrete approximations in optimal control (49M25) Unilateral problems for nonlinear elliptic equations and variational inequalities with nonlinear elliptic operators (35J87)
Related Items (11)
Cites Work
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