A sparse representation denoising algorithm for visible and infrared image based on orthogonal matching pursuit

被引：7
|
作者：
Zhang, Zhuang [1 ]
Chen, Xu [1 ]
Liu, Lei [1 ]
Li, Yefei [1 ]
Deng, Yubin [1 ]
机构：
[1] Nanjing Univ Sci & Technol, Sch Elect & Opt Engn, Dept Optoelect Technol, Nanjing 210094, Peoples R China
来源：
SIGNAL IMAGE AND VIDEO PROCESSING | 2020年 / 14卷 / 04期
关键词：
Image denoising; Sparse representation; Matching pursuit;
D O I：
10.1007/s11760-019-01606-1
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
The orthogonal matching pursuit algorithm directly samples the image signal by using the sparsity of the image signal. It uses the atom that matches the image signal feature to describe the image, which can better preserve the detailed features of the image. In this paper, an improvement of variable step size and optimized cut-off conditions is made. The experimental results show that the improved algorithm makes the denoised image clearer and have more detailed features.
引用
收藏
页码：737 / 745
页数：9
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