Improved detection of faint extended astronomical objects through statistical attribute filtering

Paul Teeninga, Ugo Moschini, Scott Trager, Michael Wilkinson

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

15 Citations (Scopus)
53 Downloads (Pure)

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.
Original languageEnglish
Title of host publicationMathematical Morphology and Its Applications to Signal and Image Processing
EditorsJón Atli Benediktsson, Jocelyn Chanussot, Laurent Najman, Hugues Talbot
PublisherSpringer
Pages157-168
Number of pages12
EditionLNCS
DOIs
Publication statusPublished - 2015
Event12th International Symposium, ISMM 2015 Reykjavik, Iceland, May 27–29, 2015 Proceedings - Reykjavik, Iceland
Duration: 27-May-201529-May-2015

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume9062

Conference

Conference12th International Symposium, ISMM 2015 Reykjavik, Iceland, May 27–29, 2015 Proceedings
Country/TerritoryIceland
CityReykjavik
Period27/05/201529/05/2015

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