ProFound: Source Extraction and Application to Modern Survey Data

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Ada Coda
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ProFound: Source Extraction and Application to Modern Survey Data

Post by Ada Coda » Fri Apr 27, 2018 6:20 pm

ProFound: Source Extraction and Application to Modern Survey Data

Abstract: ProFound detects sources in noisy images, generates segmentation maps identifying the pixels belonging to each source, and measures statistics like flux, size, and ellipticity. These inputs are key requirements of ProFit (ascl:1612.004), our galaxy profiling package; these two packages used in unison 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. ProFound 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.

Credit: Robotham, A.S.G.

Site: https://cran.r-project.org/web/packages ... index.html
http://adsabs.harvard.edu/abs/2018MNRAS.476.3137R

Bibcode: 2018ascl.soft04006R

Preferred citation method: http://adsabs.harvard.edu/abs/2018MNRAS.476.3137R

ID: ascl:1804.006
Last edited by Ada Coda on Sun May 27, 2018 6:48 pm, edited 1 time in total.
Reason: Updated code entry.

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