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Abstract: 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.
Authorship: Kayabol K., Sanz J.L., Herranz D., Kuruoglu E.E., Salerno E.,
Fuente: Monthly Notices of the Royal Astronomical Society, 2011, 415(2), 1334-1342
Publisher: Oxford University Press
Publication date: 01/08/2011
No. of pages: 9
Publication type: Article
DOI: 10.1111/j.1365-2966.2011.18783.x
ISSN: 0035-8711,1365-2966
Publication Url: https://doi.org/10.1111/j.1365-2966.2011.18783.x
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KAYABOL, K.
JOSE LUIS SANZ ESTEVEZ
DIEGO HERRANZ MUÑOZ
KURUOGLU, E. E.
E. SALERNO, E.
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