A novel denoising algorithm based on fuzzy clustering and wavelet transform

被引：0
|
作者：
Wei, Shan [1 ]
OuYang, Chun-juan [2 ]
Wei, Si-min [2 ]
机构：
[1] NE Forestry Univ, Informat & Comp Engn Inst, Harbin 150040, Peoples R China
[2] Jinggangshan Univ, Coll Informat Sci & Media, Jian 343009, Jiangxi, Peoples R China
来源：
ADVANCES IN LIQUID CRYSTALS | 2010年 / 428-429卷
关键词：
Lipschitz exponent; Fuzzy clustering; Wavelet transform; Denoising algorithm;
D O I：
10.4028/www.scientific.net/KEM.428-429.569
中图分类号：
O7 [晶体学];
学科分类号：
0702 ; 070205 ; 0703 ; 080501 ;
摘要：
According to analyzing the different wavelet coefficients' transmission property of signals and noises under different scales of the wavelet transform, LEFC denoising algorithm based on fuzzy clustering and wavelet transform is proposed. Our experimental evaluations show that the algorithm is effective and robust to restore the images compared with the other wavelet soft-thresholding algorithms. When the ratio exceeds 40 %, LEFC gives superior performance.
引用
收藏
页码：569 / +
页数：2
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