Improved Detection of Faint Extended Astronomical Objects Through Statistical Attribute Filtering

  • Paul Teeninga
  • Ugo Moschini
  • Scott C. Trager
  • Michael H. F. Wilkinson
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9082)

Abstract

In astronomy, images are produced by sky surveys containing a large number of objects. SExtractor is a widely used program for automated source extraction and cataloguing but struggles with faint extended sources. Using SExtractor as a reference, the paper describes an improvement of a previous method proposed by the authors. It is a Max-Tree-based method for extraction of faint extended sources without stronger image smoothing. Node filtering depends on the noise distribution of a statistic calculated from attributes. Run times are in the same order.

Keywords

Attribute filters Statistical tests Astronomical imaging Object detection 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Paul Teeninga
    • 1
  • Ugo Moschini
    • 1
  • Scott C. Trager
    • 2
  • Michael H. F. Wilkinson
    • 1
  1. 1.Johann Bernoulli InstituteUniversity of GroningenGroningenThe Netherlands
  2. 2.Kapteyn Astronomical InstituteUniversity of GroningenGroningenThe Netherlands

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