非下采样Contourlet变换自适应图像去噪方法  

Image de-noising algorithm using adaptive threshold based on nonsubsampled Contourlet transform

作　　者：曾业战[1] 钱盛友[1] 刘畅[1] 王岐学[1] 丁亚军[1] 

机构地区：[1]湖南师范大学物理与信息科学学院,长沙410081

出　　处：《计算机工程与应用》2010年第10期157-159,共3页Computer Engineering and Applications

摘　　要：提出了一种基于非下采样Contourlet变换的自适应图像去噪方法。首先对噪声图像进行非下采样Contourlet变换,得到各个尺度各个方向子带的系数,再根据该系数的能量自适应地调整去噪阈值。实验表明,与Contourlet多尺度阈值去噪、Contourlet自适应阈值去噪相比,该方法在保留图像边缘细节的同时,能提高图像的PSNR值,减少了Gibbs现象。A new adaptive method of image de-noising based on NonSubsampled Contourlet Transform（NSCT） is presented.Firstly, the noisy image is decomposed into a set of multiscale and multidireetional frequency subbands by NSCT,and then the threshold is adapted automatically according to the energy of subband coefficients.Compared with the multi-scale threshold using eontourlet transform and using adaptive threshold based on contourlet transform,the simulation results show that the performance of this method is superior in PSNR,meanwhile it can maintain the image edge and reduce the Gibbs phenomena.

关 键 词：图像去噪 非下采样CONTOURLET变换 阈值 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]