PATCH-BASED LOCALLY OPTIMAL DENOISING

被引:0
|
作者
Chatterjee, Priyam [1 ]
Milanfar, Peyman [1 ]
机构
[1] Univ Calif Santa Cruz, Dept Elect Engn, Santa Cruz, CA 95064 USA
关键词
Image denoising; image clustering; Wiener filter; LMMSE estimator; denoising bounds; IMAGE; SPARSE;
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
In our previous work [1], we formulated the fundamental limits of image denoising. In this paper, we propose a practical algorithm where the motivation is to realize a locally optimal denoising filter that achieves the lower bound. The proposed method is a patch-based Wiener filter that takes advantage of both geometrically and photometrically similar patches. The resultant approach has a nice statistical foundation while producing denoising results that are comparable to or exceeding the current state-of-the-art, both visually and quantitatively.
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页数:4
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