A review of source detection approaches in astronomical images
dc.contributor.author
dc.date.accessioned
2013-10-30T07:22:17Z
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2013-10-30T07:22:17Z
dc.date.issued
2012
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0035-8711
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dc.description.abstract
Astronomical images provide information about the great variety of celestial objects in the Universe, the physical processes taking place in it, and the formation and evolution of the cosmos. Great efforts are made to automatically detect stellar bodies in images due to the large volumes of data and the fact that the intensity of many sources is at the detection level of the instrument. In this paper, we review the main approaches to automated source detection. The main features of the detection algorithms are analysed and the most important techniques are classified into different strategies according to their type of image transformation and their main detection principle; at the same time their strengths and weaknesses are highlighted. A qualitative and quantitative evaluation of the results of the most representative approaches is also presented
dc.description.sponsorship
This work has been supported by Grant AYA2010-21782-C03-02 from EMCI-Ministerio de Ciencia e Innovacion. MM holds an FI grant 2011FI_B 00081
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application/pdf
dc.language.iso
eng
dc.publisher
Royal Astronomical Society
dc.relation
info:eu-repo/grantAgreement/MICINN//AYA2010-21782-C03-02/ES/FENOMENOS DE ALTA ENERGIA EN OBJETOS ESTELARES. ANALISIS DE IMAGENES MULTILONGITUD DE ONDA PARA LA DETECCION Y CARACTERIZACION DE FUENTES./
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Reproducció digital del document publicat a: http://dx.doi.org/10.1111/j.1365-2966.2012.20742.x
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© Monthly Notices of the Royal Astronomical Society, 2012, vol. 422, p. 1674-1689
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Articles publicats (D-ATC)
dc.rights
Tots els drets reservats
dc.title
A review of source detection approaches in astronomical images
dc.type
info:eu-repo/semantics/article
dc.rights.accessRights
info:eu-repo/semantics/openAccess
dc.embargo.terms
Cap
dc.type.version
info:eu-repo/semantics/publishedVersion
dc.identifier.doi
dc.identifier.idgrec
016052
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dc.relation.ProjectAcronym
dc.identifier.eissn
1365-2966