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Content Provider | IEEE Xplore Digital Library |
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Author | Chouzenoux, E. Pesquet, J.-C. Talbot, H. Jezierska, A. |
Copyright Year | 2011 |
Description | Author affiliation: Université Paris-Est, Lab. d'Informatique Gaspard Monge, UMR CNRS 8049, 77454 Marne la Vallée Cedex 2, France (Chouzenoux, E.; Pesquet, J.-C.; Talbot, H.; Jezierska, A.) |
Abstract | In this paper, we consider a class of differentiable criteria for sparse image recovery problems. The regularization is applied to a linear transform of the target image. As special cases, it includes edge preserving measures or frame analysis potentials. As shown by our asymptotic results, the considered ℓ2 — ℓ0 penalties may be employed to approximate solutions to ℓ0 penalized optimization problems. One of the advantages of the approach is that it allows us to derive an efficient Majorize-Minimize Memory Gradient algorithm. The fast convergence properties of the proposed optimization algorithm are illustrated through image restoration examples. |
Starting Page | 2717 |
Ending Page | 2720 |
File Size | 702754 |
Page Count | 4 |
File Format | |
ISBN | 9781457713040 |
ISSN | 15224880 |
e-ISBN | 9781457713033 |
e-ISBN | 9781457713026 |
DOI | 10.1109/ICIP.2011.6116230 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2011-09-11 |
Publisher Place | Belgium |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Optimization Convergence Minimization Image restoration Image edge detection Noise reduction deblurring Non-convex optimization edge preservation sparse representations Majorize-Minimize algorithms inverse problems denoising |
Content Type | Text |
Resource Type | Article |
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