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Paper: Multiscale Source Detection for Long Wavelength Astronomical Images
Volume: 485, Astronomical Data Analysis Software and Systems XXIII
Page: 421
Authors: Masias, M.; Freixenet, J.; Peracaula, M.; Lladó, X.
Abstract: The increasing number of astronomical in mid- and far-infrared, as well as in submillimeter and radio wavelengths, brings more difficulties to the already challenging task of detecting sources in an automatic way. These specific images are characterized by presenting a more complex background than in shorter wavelengths, with a higher component of noise, more noticeable flux variations and both unresolved and extended sources with a higher dynamic range. Aiming to improve the source detection efficiency in long wavelength images, in this paper we present a new approach based on the combined use of multiscale decomposition and a recently developed method called Distilled Sensing. Its application minimizes the impact of the contaminants from the background, unveiling and highlighting the sources at the same time. The experimental results achieved using infrared and radio aperture synthesis images illustrate the good performance of the approach, correctly identifying a greater percentage of true sources than using both the widely used SExtractor algorithm and the Distilled Sensing method alone.
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