CAESAR: Compact And Extended Source Automated Recognition

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Ada Coda
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CAESAR: Compact And Extended Source Automated Recognition

Post by Ada Coda » Fri Jul 13, 2018 9:56 pm

CAESAR: Compact And Extended Source Automated Recognition

Abstract: CAESAR extracts and parameterizes both compact and extended sources from astronomical radio interferometric maps. The processing pipeline is a series of stages that can run on multiple cores and processors. After local background and rms map computation, compact sources are extracted with flood-fill and blob finder algorithms, processed (selection + deblending), and fitted using a 2D gaussian mixture model. Extended source search is based on a pre-filtering stage, allowing image denoising, compact source removal and enhancement of diffuse emission, followed by a final segmentation. Different algorithms are available for image filtering and segmentation. The outputs delivered to the user include source fitted and shape parameters, regions and contours. Written in C++, CAESAR is designed to handle the large-scale surveys planned with the Square Kilometer Array (SKA) and its precursors.

Credit: Riggi, Simone

Site: https://github.com/SKA-INAF/caesar
https://ui.adsabs.harvard.edu/abs/2019PASA...36...37R

Bibcode: 2018ascl.soft07015R

Preferred citation method: https://ui.adsabs.harvard.edu/abs/2016MNRAS.460.1486R and https://ui.adsabs.harvard.edu/abs/2019PASA...36...37R

ID: ascl:1807.015
Last edited by Ada Coda on Thu Sep 10, 2020 4:41 pm, edited 1 time in total.
Reason: Updated code entry.

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