应用小波系数GSM统计模型的混合傅里叶-小波图像降噪

姜三平; 郝晓剑

doi:10.11834/jig.20090311

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专辑

应用小波系数GSM统计模型的混合傅里叶-小波图像降噪
Hybrid Fourier-wavelet Image Denoising Using Gaussian Scale Mixture Model for Wavelet Coefficients
2009年14卷第3期页码：448
纸质出版：2009
DOI： 10.11834/jig.20090311
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姜三平, 郝晓剑. 应用小波系数GSM统计模型的混合傅里叶-小波图像降噪[J]. 中国图象图形学报, 2009,14(3):448. DOI： 10.11834/jig.20090311.

JIANG Sanping, HAO Xiaojian. Hybrid Fourier-wavelet Image Denoising Using Gaussian Scale Mixture Model for Wavelet Coefficients[J]. Journal of Image and Graphics, 2009, 14(3): 448. DOI： 10.11834/jig.20090311.

摘要

提出一种混合傅里叶-小波图像降噪算法，该算法的主要步骤是：先在傅里叶域中降噪，然后在小波域中滤除剩余的噪声。小波域中要滤除的是有色噪声，为了考虑有色噪声小波系数间的相关性，采用GSM（Gaussian scale mixture）统计模型描述图像小波系数的统计特性。实验证明该算法能有效提高降噪效果。

Abstract

A hybrid Fourier-wavelet denoising method is proposed in this paper. The main steps of the proposed method are as follows. The noisy image is firstly denoised in Fourier domain. Secondly the remaining noise is removed in wavelet domain. The remaining noise is colored. In order to consider the correlation between wavelet coefficients of colored noise the Gaussian scale mixture model for images wavelet coefficients is used. Experimental results show that the proposed algorithm improves denoising performance efficiently.