Aegean: Compact source finding in radio images
Abstract: Aegean, written in python, finds compact sources within radio images by seeking out islands of pixels above a given threshold and then using the curvature of the image to determine how many Gaussian components should be used to describe the island. The Gaussian fitting is initiated with parameters determined from the curvature and intensity maps, and makes use of mpfit to perform a constrained fit. Aegean has been optimized for compact radio sources in images that have no diffuse background emission, but by pre-processing the images with a spatial filter, or by convolving an optical image with an appropriately small PSF, Aegean is able to produce excellent results in a range of applications.
Credit: Hancock, P. J.; Murphy, T.; Gaensler, B. M.; Hopkins, A.; Curran, J. R.
Site: https://github.com/PaulHancock/Aegean
http://adsabs.harvard.edu/abs/2012MNRAS.422.1812H
Bibcode: 2012ascl.soft12009H
Preferred citation method: http://adsabs.harvard.edu/abs/2012MNRAS.422.1812H and http://adsabs.harvard.edu/abs/2018PASA...35...11H
ID: ascl:1212.009