A Method for Image De-noising Based on Nonsubsampled Pyramid Contourlet Transform
一种基于非抽样LP的Contourlet变换图像去噪方法

By enriching redundancy of the contourlet transform, it is possible to weaken pseudo-Gibbs phenomena in the process of image de-noising by thresholding. In order to remove noise from image effectively and quickly, by enriching redundancy of the contourlet transform and avoiding too much data, a method for image de-noising based on non-subsampled pyramid contourlet transform is proposed. The method decomposes noisy image using nonsubsampled LP for multi-scale, and decomposes sub-image using critical sampled DFB, then performs scale related threshold for shrinkage, finally reconstructs de-noised image. Experiments compared with other related methods show that the proposed method, on the PSNR values of the de-noised images, yields improvements up to 1dB over original contourlet transform; on the time consumption, costs half less than other improved methods.