Journal Article

Joint Bayesian separation and restoration of cosmic microwave background from convolutional mixtures

K. Kayabol, J. L. Sanz, D. Herranz, E. E. Kuruoglu and E. Salerno

in Monthly Notices of the Royal Astronomical Society

Published on behalf of The Royal Astronomical Society

Volume 415, issue 2, pages 1334-1342
Published in print August 2011 | ISSN: 0035-8711
Published online July 2011 | e-ISSN: 1365-2966 | DOI: http://dx.doi.org/10.1111/j.1365-2966.2011.18783.x
Joint Bayesian separation and restoration of cosmic microwave background from convolutional mixtures

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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.

Keywords: methods: statistical; techniques: image processing; cosmic background radiation; diffuse radiation

Journal Article.  4984 words.  Illustrated.

Subjects: Astronomy and Astrophysics

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