Fractional-order total variation image denoising based on proximity algorithm

被引：76
|
作者：
Chen, Dali [1 ]
Chen, YangQuan [2 ]
Xue, Dingyu [1 ]
机构：
[1] Northeastern Univ, Coll Informat Sci & Engn, Shenyang, Liaoning, Peoples R China
[2] Univ Calif Merced, MESA Lab, Merced, CA 95343 USA
来源：
APPLIED MATHEMATICS AND COMPUTATION | 2015年 / 257卷
基金：
中国国家自然科学基金;
关键词：
Fractional calculus; Total variation; Proximity algorithm; Image denoising; TOTAL VARIATION MINIMIZATION;
D O I：
10.1016/j.amc.2015.01.012
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
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.
引用
收藏
页码：537 / 545
页数：9
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