华中师范大学学报（自然科学版）2011，Vol.45Issue(1)：37-42,6.
基于非下采样Contourlet变换的图像自适应阈值去噪算法
Adaptive thresholding for image denoising via nonsubsampled contourlet transform
金彩虹1
作者信息
- 1. 南京晓庄学院,物理与电子工程学院,南京,210017
- 折叠
摘要
Abstract
Using the advantages of translation-invariant and multidirection-selectivity which caused by nonsubsampled contourlet transform, exploiting the inter-scale and intrascale correlations of noise and available information coefficients, BayesShrink thresholds are adaptively set according to the information of subbands.This method can pick up the weak image details, it also can snuff out the big coefficients of noise.The experimental results show that this method can eliminate the pseudo-Gibbs phenomena around singularities, keep more image detail and improve the peak signal-to-noise ratio.关键词
非下采样Contourlet变换/广义高斯分布/Bayes Shrink/相关性Key words
Non-subsampled contourlet transform(NSCT)/ generalized Gaussian distribution(GGD)/ Bayes shrink/ correlation分类
信息技术与安全科学引用本文复制引用
金彩虹..基于非下采样Contourlet变换的图像自适应阈值去噪算法[J].华中师范大学学报（自然科学版）,2011,45(1):37-42,6.
