计算机与数字工程2012，Vol.40Issue(5)：111-113,151,4.
一种基于非下采样Contourlet变换的自适应阈值去噪方法
An Adaptive Threshold Denoising Method Based on Non-Sampled Contourlet Transform
摘要
Abstract
This paper presents an adaptive image de-noising method based on non-subsampled Contourlet Transform. First,using non-subsampled Contourlet transform process the noise-image, the coefficient of each scale subbands could be gotten. Then Bayesian de-noising threshold value adaptively adjusted according to the coefficient of energy in order to achieve optimal demising. Experiment results show that: Compared with the wavelet threshold denoising, non-subsampled Contourlet adaptive threshold denoising algorithm while preserving image edge details, not only can significantly improve the image SNR values, but also to reduce the Gibbs phenomenon.关键词
非下采样/Contourlet变换/阈值去噪/BayesKey words
non-subsampled/ Contourlet transform/ threshold denoising/ Bayes分类
信息技术与安全科学引用本文复制引用
黄宇达,魏霞,王迤冉,孙涛..一种基于非下采样Contourlet变换的自适应阈值去噪方法[J].计算机与数字工程,2012,40(5):111-113,151,4.基金项目
河南省科技厅基础与前沿技术研究计划项目(编号:112300410307)资助. （编号:112300410307）
