Enhancing satellite trail detection in night sky imagery with automatic salience thresholding

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dc.contributor.advisor Poovvancheri, Jiju
dc.contributor.advisor Akiyama, Yasushi, 1972-
dc.creator Kollo, Nikolaus
dc.date.accessioned 2023-09-19T14:45:06Z
dc.date.available 2023-09-19T14:45:06Z
dc.date.issued 2023-09-01
dc.identifier.uri http://library2.smu.ca/xmlui/handle/01/31839
dc.description 1 online resource (ix, 81 pages) : illustrations (some colour), charts (some colour), graphs (some colour)
dc.description Includes abstract.
dc.description Includes bibliographical references (pages 77-81).
dc.description.abstract This study proposes a novel automatic thresholding method called Automatic Salience Thresholding (AST) for creating binary masks for detecting satellite streaks in night sky imagery. The approach utilizes a combination of Gaussian filtering, a salience-based thresholding technique, shape-based morphological filtering and line detection using Probabilistic Hough Transformations to identify the satellite trail in the image. We evaluated our method on diverse datasets of night sky images containing satellite trails in varying lighting conditions. The results show that AST outperforms the compared methods when tested with several performance metrics. The proposed AST method was also used to generate annotated binary masks for Hubble Space Telescope (HST) image data with promising results. en_CA
dc.description.provenance Submitted by Greg Hilliard (greg.hilliard@smu.ca) on 2023-09-19T14:45:06Z No. of bitstreams: 1 Kollo_Nikolaus_MASTERS_2023.pdf: 62687298 bytes, checksum: 290904b20777522176e7ee363eff9ee4 (MD5) en
dc.description.provenance Made available in DSpace on 2023-09-19T14:45:06Z (GMT). No. of bitstreams: 1 Kollo_Nikolaus_MASTERS_2023.pdf: 62687298 bytes, checksum: 290904b20777522176e7ee363eff9ee4 (MD5) Previous issue date: 2023-09-01 en
dc.language.iso en en_CA
dc.publisher Halifax, N.S. : Saint Mary's University
dc.subject.lcsh Artificial satellites -- Tracking
dc.subject.lcsh Imaging systems in astronomy
dc.title Enhancing satellite trail detection in night sky imagery with automatic salience thresholding en_CA
dc.type Text en_CA
thesis.degree.name Master of Science in Applied Science
thesis.degree.level Masters
thesis.degree.discipline Mathematics and Computing Science
thesis.degree.grantor Saint Mary's University (Halifax, N.S.)
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