Papers › AutoSourceID-Light. Fast Optical Source Localization via U-Net and Laplacian of Gaussian
AutoSourceID-Light. Fast Optical Source Localization via U-Net and Laplacian of Gaussian
Fiorenzo Stoppa, Paul Vreeswijk, Steven Bloemen, Saptashwa Bhattacharyya, Sascha Caron, Guðlaugur Jóhannesson, Roberto Ruiz de Austri, Chris van den Oetelaar, Gabrijela Zaharijas, Paul. J. Groot, Eric Cator, Gijs Nelemans
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Aims. With the ever-increasing survey speed of optical wide-field telescopes and the importance of discovering transients when they are still young, rapid and reliable source localization is paramount. We present AutoSourceID-Light (ASID-L), an innovative framework that uses computer vision techniques that can naturally deal with large amounts of data and rapidly localize sources in optical images. Methods. We show that the AutoSourceID-Light algorithm based on U-shaped networks and enhanced with a Laplacian of Gaussian filter (Chen et al. 1987) enables outstanding performances in the localization of sources. A U-Net (Ronneberger et al. 2015) network discerns the sources in the images from many different artifacts and passes the result to a Laplacian of Gaussian filter that then estimates the exact location. Results. Application on optical images of the MeerLICHT telescope demonstrates the great speed and localization power of the method. We compare the results with the widely used SExtractor (Bertin & Arnouts 1996) and show the out-performances of our method. AutoSourceID-Light rapidly detects more sources not only in low and mid crowded fields, but particularly in areas with more than 150 sources per square arcminute.
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