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A quantitative analysis of source detection approaches in optical, infrared, and radio astronomical images

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Abstract

A variety of software is used to solve the challenging task of detecting astronomical sources in wide field images. Additionally, computer vision methods based on well-known or innovative techniques are arising to face this purpose. In this paper, we review several of the most promising methods that have emerged during the last few years in the field of source detection. We specifically focus on methods that have been designed to deal with images with Gaussian noise distributions. The singularity of this analysis is that the different methods have been applied to a single dataset consisting of optical, infrared, and radio images. Thus, the different approaches are applied on a level playing field, and the results obtained can be used to evaluate and compare the methods in a meaningful, quantitative way. Moreover, we present the most important strengths and weaknesses of the methods for each type of image as well as an extensive discussion where the methods with best performances are highlighted.

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Acknowledgments

This work has been supported by Grant AYA2010-21782-C03-02 from EMCI - Ministerio de Ciencia e Innovación. M. Masias holds an FI grant 2012FI_B1 00122.

We would especially like to thank to all the authors that have collaborated in this work by providing us with the codes of their approaches or the results of applying their methods to the datasets which we have selected. Without the invaluable help of Dr. Joaquín González-Nuevo (University of Cantabria), Dr. Jarvis Haupt (University of Minnesota), Dr. Dustin Lang (Princeton University), Dr. Benjamin Perret (University Paris-Est), Dr. Richard Savage (University of Warwick), Dr. Anthony Smith (University of Sussex), Albert Torrent (University of Girona), and Alexander Men’shchikov (Paris Diderot University) this work would have not been possible. Furthermore, the authors would like to thank the anonymous referee for valuable comments which have improved the paper.

This research has used data from SDSS-III. Funding for SDSS-III has been provided by the Alfred P. Sloan Foundation, the Participating Institutions, the National Science Foundation, and the U.S. Department of Energy Office of Science. The SDSS-III web site is http://www.sdss3.org/.

SDSS-III is managed by the Astrophysical Research Consortium for the Participating Institutions of the SDSS-III Collaboration including the University of Arizona, the Brazilian Participation Group, Brookhaven National Laboratory, University of Cambridge, Carnegie Mellon University, University of Florida, the French Participation Group, the German Participation Group, Harvard University, the Instituto de Astrofisica de Canarias, the Michigan State/Notre Dame/JINA Participation Group, Johns Hopkins University, Lawrence Berkeley National Laboratory, Max Planck Institute for Astrophysics, Max Planck Institute for Extraterrestrial Physics, New Mexico State University, New York University, Ohio State University, Pennsylvania State University, University of Portsmouth, Princeton University, the Spanish Participation Group, University of Tokyo, University of Utah, Vanderbilt University, University of Virginia, University of Washington, and Yale University.

This publication makes use of data products from the Wide-field Infrared Survey Explorer, which is a joint project of the University of California, Los Angeles, and the Jet Propulsion Laboratory/California Institute of Technology, funded by the National Aeronautics and Space Administration.

This research has made use of the NASA/ IPAC Infrared Science Archive, which is operated by the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration.

This research has used the facilities of the Canadian Astronomy Data Centre operated by the National Research Council of Canada with the support of the Canadian Space Agency. The research presented in this paper has used data from the Canadian Galactic Plane Survey, a Canadian project with international partners supported by the Natural Sciences and Engineering Research Council.

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  1. Department of Computer Architecture and Technology, University of Girona, Campus Montilivi—P-IV building, Girona, Spain

    M. Masias, M. Peracaula, J. Freixenet & X. Lladó

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  1. M. Masias
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  2. M. Peracaula
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  3. J. Freixenet
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  4. X. Lladó
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Correspondence to M. Masias.

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Masias, M., Peracaula, M., Freixenet, J. et al. A quantitative analysis of source detection approaches in optical, infrared, and radio astronomical images. Exp Astron 36, 591–629 (2013). https://doi.org/10.1007/s10686-013-9346-1

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