Bayesian image reconstruction in astronomy |
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| Authors: | Jorge Núñez Jorge Llacer |
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| Institution: | (1) Departament de Física de l'Atmosfera, Astronomia i Astrofisica, Universitat de Barcelona, Spain;(2) Observatorio Fabra, Barcelona, Spain;(3) Engineering Division, Lawrence Berkeley Laboratory, Berkeley, CA, USA |
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| Abstract: | This paper presents the development and testing of a new iterative reconstruction algorithm for astronomy. We propose a maximuma posteriori method of image reconstruction in the Bayesian statistical framework for the Poisson noise case. The method uses the entropy with an adjustable  sharpness parameter to define the prior probability and the likelihood with data increment parameters to define the conditional probability. The method allows us to obtain reconstructions with neither the problem of the grey reconstructions associated with the pure Bayesian reconstructions nor the problem of image deterioration, typical of the maximum likelihood method. Our iterative algorithm is fast, stable, maintains positivity, and converges to feasible images.Paper presented at the 11th European Regional Astronomical Meetings of the IAU on New Windows to the Universe, held 3–8 July, 1989, Tenerife, Canary Islands, Spain. |
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