Image denoising with neighbour dependency and customized wavelet and threshold

被引：103

作者：

Chen, GY ^{[1
]}

Bui, TD ^{[1
]}

Krzyzak, A ^{[1
]}

机构：

[1] Concordia Univ, Dept Comp Sci, Montreal, PQ H3G 1M8, Canada

来源：

PATTERN RECOGNITION | 2005年 / 38卷 / 01期

基金：

加拿大自然科学与工程研究理事会;

关键词：

image denoising; wavelets; neighbour coefficients;

D O I：

10.1016/j.patcog.2004.05.009

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Image denoising by means of wavelet transforms has been an active research topic for many years. For a given noisy image, which kind of wavelet and what threshold we use should have significant impact on the quality of the denoised image. In this paper, we use Simulated Annealing to find the customized wavelet filters and the customized threshold corresponding to the given noisy image at the same time. Also, we propose to consider a small neighbourhood around the customized wavelet coefficient to be thresholded for image denoising. Experimental results show that out, approach is better than VisuShrink, our NeighShrink with fixed wavelet, and the wiener2 filter that is available in Matlab Image Processing Toolbox. In addition, our NeighShrink with fixed wavelet already outperforms VisuShrink for all the experiments. (C) 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

引用

页码：115 / 124

页数：10

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