Maximum likelihood for Bayesian estimator based on α-stable for image

A maximum likelihood for Bayesian estimator based on α-stable is discussed. Closer to a realistic situation, and unlike previous methods used for the Bayesian estimator, for the case discussed here it is not necessary to know the variance of the noise. The parameters relative to Bayesian estimators of the model built up are carefully investigated after a discussion of α-stable 3D simulations for a maximum likelihood. The Bayesian estimator then is established. As an example, an improved Bayesian estimator that is a natural extension of the Wiener solution and other wavelet denoising (soft and hard threshold methods), is presented to illustrate our discussion.