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

来源：

2011 18TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) | 2011年

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.

引用

页数：4

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