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
收藏
页码：3278 / 3282
页数：5
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