A weighted split Bregman iteration for adaptive fractional order total variation model

被引：1
|
作者：
Li, Dazi [1 ]
Jiang, Daozhong [1 ]
Jin, Qibing [1 ]
机构：
[1] Beijing Univ Chem Technol, Coll Informat Sci & Technol, Beijing 100029, Peoples R China
来源：
PROCEEDINGS OF THE 2019 31ST CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2019) | 2019年
基金：
北京市自然科学基金; 中国国家自然科学基金;
关键词：
Split Bregman iteration; Image denoising; Fractional calculus; AFOTV; TOTAL VARIATION MINIMIZATION; IMAGE-RESTORATION; REGULARIZATION; DECOMPOSITION;
D O I：
10.1109/ccdc.2019.8832884
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Image denoising is an important branch in the process of image processing which has been widely used in various fields. This paper proposes a weighted split Bregman iteration (WSBI) algorithm for adaptive fractional order total variation model, which provides an effective method to deal with the image denoising problem. A weight coefficient w is added to the split Bregman iteration (SBI) algorithm. Compared with the ordinary SBI algorithm, this improved algorithm can achieve faster convergence and higher (PSNR) of the image by experiments. This algorithm also can well preserve the texture details of the image and avoid the staircase artifact.
引用
收藏
页码：2036 / 2041
页数：6
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