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Bedini L., Herranz D., Salerno E., Baccigalupi C., Kuruoglu E. E., Tonazzini A. Separation of correlated astrophysical sources using multiple-lag data covariance matrices. In: Eurasip Journal on Applied Signal Processing, vol. 2005 (15) pp. 2400 - 2412. Hindawi Publishing Corporation, 2005.
 
 
Abstract
(English)
This paper proposes a new strategy to separate astrophysical sources that are mutually correlated. This strategy is based on second order statistics and exploits prior information about the possible structure of the mixing matrix. Unlike ICA blind separation approaches, where the sources are assumed mutually independent and no prior knowledge is assumed about the mixing matrix, our strategy allows the independence assumption to be relaxed and performs the separation of even significantly correlated sources. Besides the mixing matrix, our strategy is also capable to evaluate the source covariance functions at several lags. Moreover, once the mixing parameters have been identified, a simple deconvolution can be used to estimate the probability density functions of the source processes. To benchmark our algorithm, we used a database that simulates the one expected from the instruments that will operate onboard ESA's Planck Surveyor Satellite to measure the CMB anisotropies all over the celestial sphere.
Subject Astrophysical imaging
Astrophysics
Blind source separation
Dependent component analysis
J.2 Physical sciences and engineering. Astronomy
I.4 Image processing and computer vision


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