Color image denoising using multivariate cauchy PDF in the contourlet domain
A new color image denoising method in the contourlet domain is proposed for reducing noise in images corrupted by Gaussian noise. This method takes into account the statistical dependencies among the contourlet coefficients of the RGB color channels. To this end, the multivariate Cauchy distribution is employed to capture these inter-channel dependencies. This model is then exploited in a Bayesian maximum a posteriori estimator to restore the clean coefficients by deriving an efficient closed-form shrinkage function. Experimental results are performed on a set of color images to evaluate the performance of the proposed denoising method. The results demonstrate that the proposed method outperforms some of the existing methods in terms of both subjective and objective criteria.