Poster abstract details

Evaluating source extraction tools
Caroline Haigh, Nushkia Chamba, Aku Venhola, Reynier Peletier, Michael Wilkinson


With the growth of the scale of imaging surveys and astronomical data, there is an increased need for automated detection and extraction of astronomical sources from images, with a high degree of accuracy. We present a comparison of several tools which have been developed to perform this task, including SourceExtractor, ProFound, NoiseChisel, and MTObjects.

In particular, we focus on evaluating performance in situations which present challenges for detection - for example, highly noisy images; faint and diffuse galaxies; extended structures, such as streams; and objects close to bright sources.

The tools will be evaluated on simulated data in order to establish a performance baseline in terms of the limits of detection. They will additionally be compared using labelled images from astronomical surveys, in order to assess how well they perform on real-world data, as well as how well they generalise to different datasets.