关键词: 多小波—非采样Contourlet变换, 图像去噪, 自适应阈值, Bayes Shrink方法

Abstract: To constrain the drawback of the image de-noising due to the lack of translation invariance and redundancy of original Contourlet transform, a new image de-noising algorithm was proposed based on multi-wavelet nonsubsampled Contourlet transform and Bayes Shrink adaptive threshold, which used multi-wavelet for multi-scale decomposing and nonsubsampled filter banks for multi-direction decomposing, then improved Bayes Shrink adaptive threshold method according to the relation among decomposed sub bands. The experimental results show that the Signal-to-Noise Ratio (SNR) values of the de-noising images are improved significantly compared with the existing algorithm. The proposed algorithm has reduced pseudo-Gibbs phenomena effectively and preserved more details and edge information of the image.

Key words: multi-wavelet nonsubsampled Contourlet transform, image de-noising, adaptive threshold, Bayes Shrink method