计算机工程与应用2012，Vol.48Issue(31)：156-160,165,6.DOI:10.3778/j.issn.1002-8331.2012.31.034
双树复小波域的邻域自适应贝叶斯收缩去噪
Neighboring adaptive BayesShrink image denoising in dual-tree complex wavelet transform
摘要
Abstract
In order to remove noise which is introduced by image acquisition or transmission more effectively, a neighboring adaptive Bayesian shrinkage image denoising method in dual-tree complex wavelet domain is proposed. This method makes use of the translation invariance and the advantage of more direction selective of the dual-tree complex wavelet transform, and the local adaptive neighborhood correlation of the coefficient is also considered. The variance of the corresponding coefficient of the appropriate neighborhood full inch window is estimated, the average of the variance which is used as the variance of the whole sub-band image is calculated using the sliding window. BayesShrink method is used to handle the wavelet coefficients to achieve efficient image denoising. The experimental results show that the proposed method gets higher PSNR and better visual expression. The denoising performance is excellent.关键词
图像去噪/双树复小波变换/邻域自适应/贝叶斯收缩Key words
image denoising/ dual-tree complex wavelet transform/ neighboring adaptive/ BayesShrink分类
信息技术与安全科学引用本文复制引用
张稳稳..双树复小波域的邻域自适应贝叶斯收缩去噪[J].计算机工程与应用,2012,48(31):156-160,165,6.基金项目
国家高技术研究发展计划(863)(No.2009AA011706). （863）
