Fractional-order total variation image denoising based on proximity algorithm

作     者：Chen, Dali Chen, YangQuan Xue, Dingyu 

作者机构：Northeastern Univ Coll Informat Sci & Engn Shenyang Liaoning Peoples R China Univ Calif Merced MESA Lab Merced CA 95343 USA 

出 版 物：《APPLIED MATHEMATICS AND COMPUTATION》 (应用数学和计算)

年 卷 期：2015年第257卷

页      面：537-545页

核心收录：

学科分类：07[理学] 070104[理学-应用数学] 0701[理学-数学] 

基　　金：National Natural Science Foundation of China Scientific Research Fund of Liaoning Provincial Education Department [L2012073] Fundamental Research Funds for the Central Universities [N130404003] 

主　　题：Fractional calculus Total variation Proximity algorithm Image denoising 

摘      要：The fractional-order total variation(TV) image denoising model has been proved to be able to avoid the blocky effect . However, it is difficult to be solved due to the non-differentiability of the fractional-order TV regularization term. In this paper, the proximity algorithm is used to solve the fractional-order TV optimization problem, which provides an effective tool for the study of the fractional-order TV denoising model. In this method, the complex fractional-order TV optimization problem is solved by using a sequence of simpler proximity operators, and therefore it is effective to deal with the problem of algorithm implementation. The final numerical procedure is given for image denoising, and the experimental results verify the effectiveness of the algorithm. (C) 2015 Elsevier Inc. All rights reserved.