Image denoising using least squares wavelet support vector machines

被引：0
|
作者：
曾国平 [1 ]
赵瑞珍 [1 ]
机构：
[1] Institute of Information Science Beijing diaotong University Beijing 100044
来源：
Chinese Optics Letters | 2007年 / 11期
关键词：
WSVM; PSNR; RBF; Image denoising using least squares wavelet support vector machines;
D O I：
暂无
中图分类号：
TP391.41 [];
学科分类号：
080203 ;
摘要：
We propose a new method for image denoising combining wavelet transform and support vector machines (SVMs).A new image filter operator based on the least squares wavelet support vector machines (LS- WSVMs) is presented.Noisy image can be denoised through this filter operator and wavelet thresholding technique.Experimental results show that the proposed method is better than the existing SVM regression with the Gaussian radial basis function (RBF) and polynomial RBF.Meanwhile,it can achieve better performance than other traditional methods such as the average filter and median filter.
引用
收藏
页码：632 / 635
页数：4
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