Restoration of images based on subspace optimization accelerating augmented Lagrangian approach

DOI10.1016/j.cam.2010.11.028zbMath1207.94006OpenAlexW2069273312WikidataQ113103588 ScholiaQ113103588MaRDI QIDQ629553

Fang Su, Dai-Qiang Chen, Li-Zhi Cheng

Publication date: 9 March 2011

Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cam.2010.11.028

zbMATH Keywords

total variationaugmented Lagrangian methodDouglas-Rachford splittingsubspace optimization

Mathematics Subject Classification ID

Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Related Items

A fast fixed point algorithm for total variation deblurring and segmentation, A subspace-accelerated split Bregman method for sparse data recovery with joint \(\ell_1\)-type regularizers, A new TV-Stokes model with augmented Lagrangian method for image denoising and deconvolution, Fast linearized alternating direction minimization algorithm with adaptive parameter selection for multiplicative noise removal

Uses Software

• NESTA
• TwIST

Cites Work

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