Image Denoising Using Bayesian Shrink Threshold Based on Weighted Adaptive Directional Lifting Wavelet Transform

摘要：

This paper introduces an image denoising method based on weighted adaptive directional lifting wavelet transform(WADL). Using this method can restrain noise from image signal and protect the texture edge simultaneity. We partition the noisy image into texture area and smooth area, following using WADL to decompose the texture area and conventional lifting wavelet to decompose the smooth area. Bayesian Shrink Threshold is used to process the wavelet coefficient. Experiment results show a good efficient.

关键词： wavelet transform weighted adaptive directional lifting wavelet transform(WADL) image denoising Bayesian shrink

作者: Quan Liu Lin Ni

作者单位: Electronic Engineering and Information Science University of Science and Technology of China Hefei, Electronic Engineering and Information Science University of Science and Technology of China Hefei,C

会议类型: 国际会议

会议名称: 2010 International Conference on Signal and Information Processing(2010年IEEE信号与信息处理国际会议 ICSIP2010)

会议地点: 长沙

会议语种:英文

页码: 470-473

在线出版日期: 2010-12-14（万方平台首次上网日期，不代表论文的发表时间）