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The process of determining the number and characteristics of sources inastronomical images is so fundamental to a large range of astronomical problemsthat it is perhaps surprising that no standard procedure has ever been definedthat has well understood properties with a high degree of statistical rigour oncompleteness and reliability. There are now a large number of commonly usedsoftware tools for accomplishing this task, typically with different toolsbeing used for images acquired using different technologies. Despite this,there have been relatively few quantitative analyses of the robustness orreliability of individual tools, or the details of the techniques theyimplement. We have an opportunity to redress this omission in the context ofsurveys planned with the Australian Square Kilometre Array Pathfinder (ASKAP).The Evolutionary Map of the Universe (EMU) survey with ASKAP, a continuumsurvey of the Southern Hemisphere up to declination +30 deg, aims to utilise anautomated source identification and measurement approach that is demonstrablyoptimal, to maximise the reliability, utility and robustness of the resultingradio source catalogues. A key stage in source extraction methods is thebackground estimation (background level and noise level) and the choice of athreshold high enough to reject false sources yet not so high that thecatalogues are significantly incomplete. In this analysis we present resultsfrom testing such algorithms as implemented in the SExtractor, Selavy(Duchamp), and sfind tools on simulated data. In particular the effects ofbackground estimation, threshold and false-discovery rate settings areexplored. For parameters that give similar completeness, the false-discoveryrate method employed by sfind results in a more reliable catalogue compared tothe peak threshold methods of SExtractor and Selavy.

The completeness and reliability of threshold and false-discovery-rate source extraction algorithms for compact continuum sources