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Improved Detection of Faint Extended Astronomical Objects through Statistical Attribute Filtering

Teeninga, P.D. (2015) Improved Detection of Faint Extended Astronomical Objects through Statistical Attribute Filtering. Bachelor's Thesis, Computing Science.

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Abstract

In astronomy, images are produced by sky surveys containing large numbers of objects. SExtractor is a widely used program for automated source extraction and cataloging but struggles with faint extended sources. Using SExtractor as a reference, the paper describes a Max-Tree-based method for improved 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 as SExtractor.

Item Type: Thesis (Bachelor's Thesis)
Degree programme: Computing Science
Thesis type: Bachelor's Thesis
Language: English
Date Deposited: 15 Feb 2018 08:05
Last Modified: 15 Feb 2018 08:05
URI: http://fse.studenttheses.ub.rug.nl/id/eprint/12972

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