Year: 2014
Author: Wei Zhu, Shi Shu, Lizhi Cheng
Advances in Applied Mathematics and Mechanics, Vol. 6 (2014), Iss. 2 : pp. 145–164
Abstract
In this paper, we propose a fast proximity point algorithm and apply it to total variation (TV) based image restoration. The novel method is derived from the idea of establishing a general proximity point operator framework based on which new first-order schemes for total variation (TV) based image restoration have been proposed. Many current algorithms for TV-based image restoration, such as Chambolle's projection algorithm, the split Bregman algorithm, the Bermúdez-Moreno algorithm, the Jia-Zhao denoising algorithm, and the fixed point algorithm, can be viewed as special cases of the new first-order schemes. Moreover, the convergence of the new algorithm has been analyzed at length. Finally, we make comparisons with the split Bregman algorithm which is one of the best algorithms for solving TV-based image restoration at present. Numerical experiments illustrate the efficiency of the proposed algorithms.
You do not have full access to this article.
Already a Subscriber? Sign in as an individual or via your institution
Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/10.4208/aamm.2013.m175
Advances in Applied Mathematics and Mechanics, Vol. 6 (2014), Iss. 2 : pp. 145–164
Published online: 2014-01
AMS Subject Headings: Global Science Press
Copyright: COPYRIGHT: © Global Science Press
Pages: 20
Keywords: Proximity point operator image restoration total variation first-order schemes.
Author Details
-
Recent Advances in Theoretical, Applied, Computational and Experimental Mechanics
Fluid–Structure Interaction Dynamics of a Flexible Foil in Low Reynolds Number Flows
Bose, Chandan | Sarkar, Sunetra | Gupta, Sayan2020
https://doi.org/10.1007/978-981-15-1189-9_37 [Citations: 1] -
New regularization method and iteratively reweighted algorithm for sparse vector recovery
Zhu, Wei | Zhang, Hui | Cheng, LizhiApplied Mathematics and Mechanics, Vol. 41 (2020), Iss. 1 P.157
https://doi.org/10.1007/s10483-020-2561-6 [Citations: 1]