Wavelet transforms and denoising algorithms

被引：0

作者：

Berkner, K ^{[1
]}

Wells, RO ^{[1
]}

机构：

[1] Rice Univ, Dept Math, Computat Math Lab, Houston, TX 77251 USA

来源：

CONFERENCE RECORD OF THE THIRTY-SECOND ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS & COMPUTERS, VOLS 1 AND 2 | 1998年

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper addresses generalizations of the Donoho-Johnstone denoising method which is suited for additive Gaussian White noise and uses orthogonal wavelet transforms. We discuss the effects the choice of the wavelet transform has in wavelet shrinkage assuming the noise model to be Gaussian White noise. In addition we formulate some more general noise models that arise from real world data such as medical images and seismic data.

引用

页码：1639 / 1643

页数：5

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