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dc.contributor.authorRobotham, A. S. G.
dc.contributor.authorDavies, L. J. M.
dc.contributor.authorDriver, S. P.
dc.contributor.authorKoushan, S.
dc.contributor.authorTaranu, D. S.
dc.contributor.authorCasura, S.
dc.contributor.authorLiske, J.
dc.date.accessioned2018-04-24T10:30:16Z
dc.date.available2018-04-24T10:30:16Z
dc.date.issued2018-05
dc.identifier.citationRobotham , A S G , Davies , L J M , Driver , S P , Koushan , S , Taranu , D S , Casura , S & Liske , J 2018 , ' ProFound : source extraction and application to modern survey data ' , Monthly Notices of the Royal Astronomical Society , vol. 476 , no. 3 , pp. 3137-3159 . https://doi.org/10.1093/mnras/sty440en
dc.identifier.issn0035-8711
dc.identifier.otherPURE: 252910571
dc.identifier.otherPURE UUID: d4d06958-5189-432a-ab04-eaf29c3f709d
dc.identifier.otherArXiv: http://arxiv.org/abs/1802.00937v1
dc.identifier.otherScopus: 85051851898
dc.identifier.urihttp://hdl.handle.net/10023/13191
dc.descriptionParts of this research were conducted by the Australian Research Council Centre of Excellence for All-sky Astrophysics (CAASTRO), through project number CE110001020.en
dc.description.abstractWe introduce ProFound, a source finding and image analysis package. ProFound provides methods to detect sources in noisy images, generate segmentation maps identifying the pixels belonging to each source, and measure statistics like flux, size and ellipticity. These inputs are key requirements of ProFit, our recently released galaxy profiling package, where the design aim is that these two software packages will be used in unison to semi-automatically profile large samples of galaxies. The key novel feature introduced in ProFound is that all photometry is executed on dilated segmentation maps that fully contain the identifiable flux, rather than using more traditional circular or ellipse based photometry. Also, to be less sensitive to pathological segmentation issues, the de-blending is made across saddle points in flux. We apply ProFound in a number of simulated and real world cases, and demonstrate that it behaves reasonably given its stated design goals. In particular, it offers good initial parameter estimation for ProFit, and also segmentation maps that follow the sometimes complex geometry of resolved sources, whilst capturing nearly all of the flux. A number of bulge-disc decomposition projects are already making use of the ProFound and ProFit pipeline, and adoption is being encouraged by publicly releasing the software for the open source R data analysis platform under an LGPL-3 license on GitHub (github.com/asgr/ProFound).
dc.language.isoeng
dc.relation.ispartofMonthly Notices of the Royal Astronomical Societyen
dc.rights© 2018 The Author(s). Published by Oxford University Press on behalf of the Royal Astronomical Society. This work has been made available online in accordance with the publisher’s policies. This is the author created, accepted version manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at https://doi.org/10.1093/mnras/sty440en
dc.subjectMethods: data analysisen
dc.subjectTechniques: image processingen
dc.subjectTechniques: photometricen
dc.subjectQC Physicsen
dc.subjectQA76 Computer softwareen
dc.subjectDASen
dc.subject.lccQCen
dc.subject.lccQA76en
dc.titleProFound : source extraction and application to modern survey dataen
dc.typeJournal articleen
dc.description.versionPostprinten
dc.contributor.institutionUniversity of St Andrews.School of Physics and Astronomyen
dc.identifier.doihttps://doi.org/10.1093/mnras/sty440
dc.description.statusPeer revieweden


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