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) |
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| 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: | https://fse.studenttheses.ub.rug.nl/id/eprint/12972 |
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