Signal denoising using neighbouring dual-tree complex wavelet coefficients

被引：23

作者：

Chen, G. ^{[1
]}

Zhu, W. -P. ^{[1
]}

机构：

[1] Concordia Univ, Dept Elect & Comp Engn, Montreal, PQ H3G 1M8, Canada

来源：

IET SIGNAL PROCESSING | 2012年 / 6卷 / 02期

基金：

加拿大自然科学与工程研究理事会;

关键词：

BIVARIATE SHRINKAGE; IMAGE; MULTIWAVELETS; DEPENDENCY;

D O I：

10.1049/iet-spr.2010.0262

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Denoising is a very important preprocessing step in signal/image processing. In this study, a new signal denoising algorithm is proposed by using neighbouring wavelet coefficients. The dual-tree complex wavelet transform is employed because of its property of approximate shift invariance, which is very important in signal denoising. Both translation-invariant (TI) and non-TI versions of the denoising algorithm are considered. Experimental results show that the proposed method outperforms other existing methods in the literature for denoising both artificial and real-life noisy signals.

引用

页码：143 / 147

页数：5

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