A Novel Adaptive Non Local Means For Image De-Noising

被引：2

作者：

Peter, Dinesh J. ^{[1
]}

Ramya, R. ^{[1
]}

机构：

[1] Karunya Univ, Dept Informat Technol, Coimbatore 641114, Tamil Nadu, India

来源：

INTERNATIONAL CONFERENCE ON MODELLING OPTIMIZATION AND COMPUTING | 2012年 / 38卷

关键词：

Clustering; De-noising; Segmentation; k-means; NL-means;

D O I：

10.1016/j.proeng.2012.06.379

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

This paper presents an adaptive non-local means filter for image de-noising in a novel approach that reduces considered amount of noise in an image acquired by digital still cameras. The proposed adaptive method is based on intensity level image segmentation by k-means clustering. This adaptive method provides only "right" pixels for NL-means averaging process in the square neighbourhood. It gives better result in visual quality and numerical results compare to classical NL-means filter. (C) 2012 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of Noorul Islam Centre for Higher Education

引用

页码：3278 / 3282

页数：5

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