Locally Adaptive Bivariate Shrinkage Algorithm for Image Denoising Based on Nonsubsampled Contourlet Transform
The Nonsubsampled Contourlet Transform (NSCT) is a new image representation approach that has sparser representation at both spatial and directional resolution as well as captures smooth contours in images. There are strong correlations between the parent and child coefficients of NSCT. Considering inter-scale and intra-scale dependency, in this paper, a method for image denoising in NSCT domain by using locally adapt bivariate shrinkage algorithm is proposed. This scheme achieved estimation results for images that are corrupted by additive Gaussian white noise (AGWN) and compares with NSCT-LAS, BivShrink and BLS-GSM. Experimental results show the proposed scheme can receive better denoising results.
lmage denoising NSCT Bivariate shrinkage Algorithm
Hongzhi Wang Cai he Lu wei
College of computer Science and Engineering Changchun University of Technology, Changchun Jilin, China, 130012
国际会议
长春
英文
33-36
2010-08-24（万方平台首次上网日期，不代表论文的发表时间）