PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Kayabol K., Kuruoglu E. E., Sankur B. Astrophysical component separation with Langevin sampler. In: SIU 2009 - IEEE 17th Signal Processing and Communications Applications Conference (Antalya/Turkey, 9-11 April 2009). Proceedings, pp. 495 - 498. University of Kocaeli, 2009.
 
 
Abstract
(English)
We propose a new Monte Carlo method for the astrophysical image separation problem. In this Bayesian simulation context, we used Langevin stochastic equation to generate the samples instead of the conventional random walk model. Since the samples are produced in parallel and tested pixel-by-pixel in the Metropolis-Hasting scheme, there is a significant gain in the processing time at the cost of a modest decrease in performance. An additional advantage of our method is the on-line estimation of the Markov Random Fields (MRF) model parameters.
URL: http://ieeexplore.ieee.org/xpl/tocresult.jsp?isnumber=5136316&isYear=2009&count=254&page=2&ResultStart=50
DOI: 10.1109/SIU.2009.5136378
Subject Source separation
Markov Chain Monte Carlo
Langevin equation
Astrophysical images
I.4 Image Processing and Computer Vision
J.2 Physical Sciences and Engineering
62M40 Random fields; image analysis
65Cxx Probabilistic methods, simulation and stochastic differential equations


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