Title
A relaxed Newton–Picard like method for Huber variant of total variation based image restoration
Abstract
In this paper, we propose an effective iteration method for Huber variant of total variation based image restoration by exploiting the structure of the problem. We call the proposed method relaxed Newton–Picard like method. This method is easy to implement and cost-effective. We prove the convergence of the method by using the theory on semismooth functions. Experimental results show that the proposed method is more efficient than the alternating minimization method based on multiplicative half-quadratic reformulation and is competitive with the state of the art alternating direction method of multipliers.
Year
DOI
Venue
2019
10.1016/j.camwa.2019.02.021
Computers & Mathematics with Applications
Keywords
Field
DocType
Image restoration,Gaussian noise,Total variation,Newton–Picard method,Iterative algorithm,Regularization
Convergence (routing),Applied mathematics,Mathematical optimization,Multiplicative function,Iterative method,Minification,Image restoration,Mathematics
Journal
Volume
Issue
ISSN
78
1
0898-1221
Citations 
PageRank 
References 
0
0.34
0
Authors
1
Name
Order
Citations
PageRank
Jianjun Zhang142.21