Image Denosing Based on Wavelet Regularity and Bayesian Regulation
基于小波域正则化和贝叶斯规则的图像恢复算法

This work puts forward a new algorithm that the wavelet transformation regularity for image restoration connects with Bayesian statistic modeling, as to make an image denosing. A regularized image restoration is the optimization for some conditional constraint, and the selection of wavelet coefficients based Bayesian statistic is on the image random field view. We could dialectically give the processing about choices of regularity coefficients, operators and the calculation of distributed prior-models according to the two former conditions.