Image denoising based on local adaptive multi-scale wavelet least squares support vector regression(MWLS_SVR)

被引：0

作者：

Wu, Dingxue ^{[1
]}

Peng, Daiqiang ^{[1
]}

Tian, Jinwen ^{[1
]}

机构：

[1] Huazhong Univ Sci & Technol, Inst Pattern Recognit & Artificial Intelligence, Wuhan 430074, Hubei, Peoples R China

来源：

MIPPR 2007: AUTOMATIC TARGET RECOGNITION AND IMAGE ANALYSIS; AND MULTISPECTRAL IMAGE ACQUISITION, PTS 1 AND 2 | 2007年 / 6786卷

关键词：

multi-scale wavelet least square support vector machines; image denoising;

D O I：

10.1117/12.747962

中图分类号：

TP7 [遥感技术];

学科分类号：

081102 ; 0816 ; 081602 ; 083002 ; 1404 ;

摘要：

Rather than attempting to separate signal from noise in the spatial domain, it is often advantageous to work in a transform domain. Building on previous work, a novel denoising method based on local adaptive multi-scale wavelet least squares support vector regression is proposed. Investigation on real images contaminated by Gaussian noise has demonstrated that the proposed method can achieve an acceptable trade off between the noise removal and smoothing of the edges and details.

引用

页数：6

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