Inter-scale Correlation Image Denoising Based on Non-aliasing Contourlet Transform

A novel image denoising method based on non-aliasing Contourlet transform(NACT) is presented according to coefficient inter-scale correlation. A noisy image was decomposed into a low frequency approximation sub-image and a series of high frequency detail sub-images at different scale and direction via NACT. In the transform domain, the inter-scale correlation of the signal coefficients was strong, and there was weak inter-scale correlation for noise coefficients, so the noise in the high frequency detail sub-images was removed by using of non-Gaussian bivariate model. Experimental results show that the proposed scheme has higher operational efficiency, and it can overcome the aliasing in Contourlet transform and avoid ¿scratching¿ phenomenon in the reconstructed image. Whether PSNR index or in visual effect, the proposed scheme outperforms the traditional Contourlet transform denoising, Contourlet domain HMT denoising and the hard threshold denoising based on no-aliasing Contourlet transform, and can achieve an excellent balance between suppress noise effectively and preserve as many image details and edges as possible.