A new efficient variational model for multiplicative noise removal

被引:5
|
作者
Bai, Lufeng [1 ,2 ]
Liu, Fang [1 ]
Tan, Shenyang [2 ]
机构
[1] Nanjing Univ Sci, Sch Sci, Technol, Nanjing, Peoples R China
[2] Nanjing Univ Sci, Taizhou Inst Sci, Technol, Nanjing, Peoples R China
关键词
Primal-dual method; multiplicative noise; Taylor approximation model; variational model; semi-implicit iteration; strictly convex; RESTORATION; IMAGES;
D O I
10.1080/00207160.2019.1622688
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
In this paper, based on the approximation of the Taylor expansion, a novel fidelity term is formulated. We propose a new variational image restoration model to recover an image from its multiplicative noised version. We show that the proposed model is strictly convex and has a unique solution so that the model can be performed by the primal-dual method. Compared with other models, the proposed model is able to not only deal with various problems of different type noises, such as the multiplicative Beta noise, F noise, Gaussian noise, but also take significantly less computational time.
引用
收藏
页码:1444 / 1458
页数:15
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