Bayesian Image Denoising Based on Joint Probability Distribution Model in Wavelet Domain

Based on the inter-and intra-scale coefficients' decorrelating but also the dependent properties of wavelet-based decomposed image, a new local non-Gaussian joint probability distribution model is proposed, and following that, a new closed maximum a posteriori(MAP) estimating formula is derived under the Bayesian estimation theory by using this model as the prior distribution model. At last, several numerical examples are given, the experiments show the denoised images have not only a lower mean-square error(MSE) ,but also a better ability of edge preservation and enhancement.