Non-smooth SOR for \(L ^{1}\)-fitting: convergence study and discussion of related issues

DOI10.1007/s10915-008-9229-1zbMath1203.65070OpenAlexW1966462666WikidataQ110084523 ScholiaQ110084523MaRDI QIDQ618409

Roland Glowinski, A. Ivannikov, Tuomo Valkonen, Tommi Kärkkäinen

Publication date: 16 January 2011

Published in: Journal of Scientific Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10915-008-9229-1

zbMATH Keywords

denoisingconvex analysisnon-smooth objective functionover-relaxation

Mathematics Subject Classification ID

Numerical optimization and variational techniques (65K10) Computing methodologies for image processing (68U10) Iterative numerical methods for linear systems (65F10) Information theory (general) (94A15)

Related Items (2)

Looking for the best constant in a Sobolev inequality: a numerical approach ⋮ Convergence of the modified SOR–Newton method for non-smooth equations

Cites Work

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• Augmented Lagrangian active set methods for obstacle problems
• Denoising of smooth images using \(L^{1}\)-fitting
• Structure-texture image decomposition -- modeling, algorithms, and parameter selection
• Dynamic Scaling of Growing Interfaces
• Convergence of a SOR-Weiszfeld Type Algorithm for Incomplete Data Sets
• Minimizers of Cost-Functions Involving Nonsmooth Data-Fidelity Terms. Application to the Processing of Outliers
• Robust Statistics
• Building blocks for odd-even multigrid with applications to reduced systems

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