Grey theory applied in non-subsampled Contourlet transform

Abstract

This study mainly discussed the application of grey theory in the non-subsampled Contourlet domain. The new algorithm combined the excellent characteristics of the non-subsampled Contourlet transform and grey theory in image denoising. The total variation model is used first to modify the noised image in order to reduce the pseudo-Gibbs artifacts. In the high-frequency area, the grey relational methods are proposed in the current study. The authors combined the two methods in the high-frequency processing and proposed an improved model that is superior to others. Finally, they presented some experimental results to compare with the non-local means algorithm. The comparisons showed very good performance of the proposed model. The proposed method can preserve most important information of image.