COMBINED NON-LOCAL AVERAGING AND INTERSECTION OF CONFIDENCE INTERVALS FOR IMAGE DE-NOISING

被引：6

作者：

Bilcu, Radu Ciprian ^{[1
]}

Vehvilainen, Markku ^{[1
]}

机构：

[1] Nokia Res Ctr, Interact Core Technol Ctr, Tampere 33720, Finland

来源：

2008 15TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1-5 | 2008年

关键词：

Image processing; image de-noising; non-local means; intersection of confidence intervals;

D O I：

10.1109/ICIP.2008.4712110

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The Non-Local means (NL-means) algorithm was recently introduced and shown state of the art performance in image denoising. However the computational complexity of the NL-means is very high which can prevent its implementation into products. In this paper we propose a method which retains the excellent de-noising characteristics of the NL-means algorithm but with much less computational complexity. Comparison between our method, the NL-means algorithm and other fast NL-means based approaches is illustrated through several experiments.

引用

页码：1736 / 1739

页数：4

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