SExtractor: Software for source extraction

¹ Institut d'Astrophysique de Paris, 98bis Boulevard Arago, 75014 Paris, France
² European Southern Observatory, Casilla 19001, Santiago 19, Chile

Corresponding author: Send offprint request to: e-mail: bertin@iap.fr

Received: 18 July 1995
Accepted: 17 August 1995

Abstract

We present the automated techniques we have developed for new software that optimally detects, deblends, measures and classifies sources from astronomical images: SExtractor (Source Extractor ). We show that a very reliable star/galaxy separation can be achieved on most images using a neural network trained with simulated images. Salient features of SExtractor include its ability to work on very large images, with minimal human intervention, and to deal with a wide variety of object shapes and magnitudes. It is therefore particularly suited to the analysis of large extragalactic surveys.