Astrophysical image denoising using bivariate isotropic cauchy distributions in the undecimated wavelet domain

Within the framework of wavelet analysis, we describe a novel technique for removing noise from astrophysical im- ages. We design a Bayesian estimator, which relies on a particular member of the family of isotropic ®-stable dis- tributions, namely the bivariate Cauchy density. Using the bivariate Cauchy model we develop a noise-removal pro- cessor that takes into account the interscale dependencies of wavelet coe±cients. We show through simulations that our proposed technique outperforms existing methods both visually and in terms of root mean squared error.