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Proceedings Paper

Deblending of the UV photometry in GALEX deep surveys using optical priors in the visible wavelengths
Author(s): M. Guillaume; A. Llebaria; D. Aymeric; S. Arnouts; B. Milliard
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Paper Abstract

The GALEX mission of NASA, is collecting an unprecedent set of astronomical UV data in the far and the near UV range. The telescope measures the full sky in a continuous automatic scan. Knowing the attitude data, local images are simultaneously extracted and corrected for smearing and instrumental effects. Final UV images show, by far, a lower resolution than their visible counterpart. It originates blends, ambiguities and missidentifications of the astronomical sources. Our purpose is to deduce from the UV image the UV photometry of the visible objets through a bayesian approach, using the visible data (catalog and image) as the starting reference for the UV analysis. For the feasibility reasons as the deep field images are very large, a segmentation procedure has been defined to manage the analysis in a tractable form. The present paper discusses all these aspects and details the full method and performances.

Paper Details

Date Published: 17 February 2006
PDF: 10 pages
Proc. SPIE 6064, Image Processing: Algorithms and Systems, Neural Networks, and Machine Learning, 606411 (17 February 2006); doi: 10.1117/12.650684
Show Author Affiliations
M. Guillaume, Institut Fresnel, Univ. Aix Marseille III (France)
A. Llebaria, LAM-OAMP, CNRS (France)
D. Aymeric, CUST, Univ. Blaise Pascal (France)
S. Arnouts, LAM-OAMP, CNRS (France)
B. Milliard, LAM-OAMP, CNRS (France)

Published in SPIE Proceedings Vol. 6064:
Image Processing: Algorithms and Systems, Neural Networks, and Machine Learning
Nasser M. Nasrabadi; Edward R. Dougherty; Jaakko T. Astola; Syed A. Rizvi; Karen O. Egiazarian, Editor(s)

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