A Comparative Study on Thresholding Methods in Wavelet-based Image Denoising

被引：28
|
作者：
Xiao, Fei [1 ]
Zhang, Yungang [1 ]
机构：
[1] Yunnan Normal Univ, Dept Comp Sci, Kunming 650500, Peoples R China
来源：
CEIS 2011 | 2011年 / 15卷
关键词：
Discrete wavelet transform; image denoising; thresholding; SHRINKAGE;
D O I：
10.1016/j.proeng.2011.08.749
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Wavelet-based image denoising is an important technique in the area of image noise reduction. Wavelets have their natural ability to represent images in a very sparse form which is the foundation of wavelet-based denoising through thresholding. This paper explores properties of several representative thresholding techniques in wavelets denoising, such as VisuShrink, SureShrink, BayesShrink and Feature Adaptive Shrinkage. A quantitative comparison between these techniques through PSNR (Peak Signal-to-Noise Ratio) is also given. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of [CEIS 2011]
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页数：6
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