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Proceedings Paper

Resolution Classifier
Author(s): Francisco Valdes
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Paper Abstract

A new automated astronomical image classifier is described. The classifier is of the Bayesian type using maximum-likelihood template fitting with Poisson noise. The method's advantages are that there is no need for an explicit galaxy model, it provides a continuous spectnirn between totally unresolved objects and obviously diffuse resolved galaxies, and it can assign a probability to the classification. The continuous nature of the classifier allows identification of intermediate types such as stellar objects with faint nebulosity and galaxies with bright unresolved nuclei. The ability to assign a probability to each classification allows a determination of when the noise, plate quality, and scale of the images no longer gives a sensible division of stars and galaxies. Also the probability allows the weighting of objects in statistical studies relying on this separation. The method is applied to the catalog of 4-meter prime focus plates automatically reduced by the FO CA S system. It is compared with the hypersurface clustering classifier of Jarvis and Tyson.

Paper Details

Date Published: 16 November 1982
PDF: 8 pages
Proc. SPIE 0331, Instrumentation in Astronomy IV, (16 November 1982); doi: 10.1117/12.933489
Show Author Affiliations
Francisco Valdes, Bell Laboratories (United States)


Published in SPIE Proceedings Vol. 0331:
Instrumentation in Astronomy IV
David L. Crawford, Editor(s)

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