Nonmonotone and monotone active-set methods for image restoration. II: Numerical results.

DOI10.1023/A:1004607123926zbMath1050.90033OpenAlexW167052753WikidataQ109967927 ScholiaQ109967927MaRDI QIDQ1586817

K. Majava, Tommi Kärkkäinen

Publication date: 6 March 2001

Published in: Journal of Optimization Theory and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1023/a:1004607123926

zbMATH Keywords

Image restoration, bounded variations, active-set methods

Mathematics Subject Classification ID

Applications of mathematical programming (90C90) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Related Items (5)

MLP in Layer-Wise Form with Applications to Weight Decay ⋮ Fast algorithm for image denoising with different boundary conditions ⋮ Denoising of smooth images using \(L^{1}\)-fitting ⋮ On a nonlinear multigrid algorithm with primal relaxation for the image total variation minimisation ⋮ Nonmonotone and monotone active-set method for image restoration. I: Convergence analysis.

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• Nonmonotone and monotone active-set method for image restoration. I: Convergence analysis.
• An active set strategy based on the augmented Lagrangian formulation for image restoration
• A Nonlinear Primal-Dual Method for Total Variation-Based Image Restoration
• Fast, robust total variation-based reconstruction of noisy, blurred images
• Iterative Methods for Total Variation Denoising

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