PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Kayabol K., Sanz J. L., Herranz D., Kuruoglu E. E., Salerno E. Joint Bayesian separation and restoration of CMB from convolutional mixtures. Monthly Notices of the Royal Astronomical Society. Preprint, 2011.
 
 
Abstract
(English)
We propose a Bayesian approach to joint source separation and restoration for astrophysical diff use sources. We constitute a prior statistical model for the source images by using their gradient maps. We assume a t-distribution for the gradient maps in di fferent directions, because it is able to fit both smooth and sparse data. A Monte Carlo technique, called Langevin sampler, is used to estimate the source images and all the model parameters are estimated by using deterministic techniques.
URL: http://arxiv.org/abs/1101.1397
Subject Bayesian source separation
Astrophysical images
Student t distribution
Langevin sampler
J.2 Physical Sciences and Engineering


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