Superpixels-based Non-local Means Image Denoising

被引：0
|
作者：
Liu, Weihua [1 ,2 ]
Wu, Shiqian [2 ]
机构：
[1] Xian Univ Posts & Telecommun, Sch Telecommun & Informat Engn, Xian, Peoples R China
[2] Wuhan Univ Sci & Technol, Sch Machinery & Automat, Wuhan, Peoples R China
来源：
PROCEEDINGS OF THE 2016 IEEE 11TH CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA) | 2016年
关键词：
non-local means; image denoising; superpixel; simple linear iterative clustering; adaptive patch; ALGORITHM;
D O I：
暂无
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：
Although the non-local means method achieves high performance in image denoising, its computation is very expensive. In this paper, we propose to reduce the complexity based on superpixel clustering. The idea is to first divide whole image into some superpixels based on pixels' similar geometry structure. Then the selection of similar patches is conducted in every superpixel. Experiments show that the proposed method has good denoising performance while the computation complexity is decreased in comparison with other algorithms.
引用
收藏
页码：673 / 677
页数：5
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