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Deconvolution of astronomical adaptive optics images

Published online by Cambridge University Press:  28 May 2003

Claude Aime ,
Rémi Soummer ,
T. Fusco ,
L. Mugnier ,
J.-M. Conan ,
G. Rousset ,
F. Marchis ,
G. Chauvin ,
A.-M. Lagrange  and
D. Mouillet
G. Rousset
Affiliation:
Office National d'Études et de Recherches Aérospatiales (ONERA), France
F. Marchis
Affiliation:
University of California, Berkeley, CA 94720, USA
A.-M. Lagrange
Affiliation:
Laboratoire d'Astrophysique de Grenoble, France
D. Mouillet
Affiliation:
Laboratoire Astrophysique, Observatoire Midi-Pyrénées, France
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Abstract

Deconvolution is a necessary tool for the exploitation of adaptive opticscorrected images, because the correction is partial. The Maximum APosteriori (MAP) framework is used to derive a deconvolution method(MISTRAL) thatcombines the data with our knowledge of the noise statistics as well as ourprior information about the object and the variability of the Point SpreadFunction. The deconvolution of experimental and scientific data illustrates the capabilitiesof this method.

Information

Type
Research Article
Information
European Astronomical Society Publications Series , Volume 8: Astronomy with High Contrast Imaging , 2003 , pp. 259 - 271
Copyright
© EAS, EDP Sciences, 2003

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