Adaptive thresholding for image denoising via sationary Contourlet transform
基于平稳Contourlet变换的自适应阈值去噪*

Stationary Contourlet transform with shifl-invariant was applied to image denoising, which could capture the intrinsic geometrical structure of image. Meanwhile, the adaptive Bayes threshold with hard threshold function was implemented to image denoising. The experimental results show that the method can get higher PSNR value and better visual effect compared with other methods.