Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/26295
Title: Smoothing nonlinear conjugate gradient method for image restoration using nonsmooth nonconvex minimization
Authors: Chen, X 
Zhou, W
Keywords: Image restoration
Nonlinear conjugate gradient method
Nonsmooth and nonconvex optimization
Potential function
Regularization
Smooth approximation
Issue Date: 2010
Source: SIAM Journal on imaging sciences, 2010, v. 3, no. 4, p. 765-790 How to cite?
Journal: SIAM Journal on Imaging Sciences 
Abstract: Image restoration problems are often converted into large-scale, nonsmooth, and nonconvex optimization problems. Most existing minimization methods are not efficient for solving such problems. It is well known that nonlinear conjugate gradient methods are preferred to solve large-scale smooth optimization problems due to their simplicity, low storage, practical computation efficiency, and nice convergence properties. In this paper, we propose a smoothing nonlinear conjugate gradient method where an intelligent scheme is used to update the smoothing parameter at each iteration and guarantees that any accumulation point of a sequence generated by this method is a Clarke stationary point of the nonsmooth and nonconvex optimization problem. Moreover, we present a class of smoothing functions and show their approximation properties. This method is easy to implement without adding any new variables. Three image restoration problems with different pixels and different regularization terms are used in numerical tests. Experimental results and comparison with the continuation method in show the efficiency of the proposed method.
URI: http://hdl.handle.net/10397/26295
ISSN: 1936-4954
DOI: 10.1137/080740167
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

37
Last Week
6
Last month
3
Citations as of Apr 22, 2017

WEB OF SCIENCETM
Citations

36
Last Week
1
Last month
2
Citations as of Apr 19, 2017

Page view(s)

28
Last Week
9
Last month
Checked on Apr 23, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.