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 cosmic microwave background from convolutional mixtures. In: Monthly Notices of the Royal Astronomical Society, vol. 415 (2) pp. 1334 - 1342. Wiley, 2011.
 
 
Abstract
(English)
We propose a Bayesian approach to joint source separation and restoration for astrophysical diffuse 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 different 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://onlinelibrary.wiley.com/doi/10.1111/j.1365-2966.2011.18783.x/pdf
DOI: 10.1111/j.1365-2966.2011.18783.x
Subject Astrophysical component separation
J.2 Physical sciences and engineering. Astronomy


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