Wavelet domain blind image separation
Mahieddine M. Ichir, Ali Mohammad‐Djafari · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2003
In this work, we consider the problem of blind source separation in the wavelet domain via a Bayesian estimation framework. We use the sparsity and multiresolution properties of the wavelet coefficients to model their distribution by heavy tailed prior probability laws: the generalized exponential family and the Gaussian mixture family. Appropriate MCMC algorithms are developed in each case for the estimation purposes and simulation results are presented for comparaison.