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Mathematical Morphology - Theory and Applications

Editor-in-Chief: Chanussot, Jocelyn

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Emerging Science

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2353-3390
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Statistical attribute filtering to detect faint extended astronomical sources

Paul Teeninga / Ugo Moschini / Scott C. Trager / Michael H.F. Wilkinson
Published Online: 2016-03-30 | DOI: https://doi.org/10.1515/mathm-2016-0006

Abstract

In astronomy, sky surveys contain a large number of light-emitting sources, often with intensities close to the noise level. Automatic extraction of astronomical objects is therefore needed. SExtractor is a widely used program for automated source extraction and cataloguing, but it is not optimal with faint extended sources. Using SExtractor as a reference, the paper describes an improvement of a previous method proposed by the authors. It is a Max-Tree-based method for extraction of faint extended sources without using a stronger image smoothing. The Max-Tree structure is a hierarchical representation of an image, in which attributes can be computed in every node. Object detection is performed on the nodes of the tree and it relies on the distribution of a statistic calculated using the power attribute, compared to the expected distribution in case of noise. Statistical tests are presented, a comparison with the object extraction of SExtractor is shown and results are discussed.

Keywords: Attribute filters; statistical tests; astronomical imaging; object detection

References

  • [1] K. N. Abazajian et al., Astrophys. J. Suppl. S., 2009, 182, 2 Google Scholar

  • [2] C. Berger, T. Géraud, R. Levillain, N. Widynski, A. Baillard, E. Bertin, Proceedings of International Conference on Image Processing, Sep. 16-19, 2007, San Antonio, TX, USA 41 Google Scholar

  • [3] E. Bertin, S. Arnouts, Astron. Astrophys. Suppl. S., 1996, 117, 393 Google Scholar

  • [4] E. Breen, R. Jones, Comput. Vis. Image. Und., 1996, 64, 3 Google Scholar

  • [5] R. B. D’Agostino, A. Belanger, R. B. D’Agostino Jr, Am. Stat., 1990, 44, 4 Google Scholar

  • [6] J. Gunn et al., Astron. J., 1998, 116, 6 Google Scholar

  • [7] M. Masias, J. Freixenet, X. Lladó, M. Peracaula, Mon. Not. R. Astron. Soc., 2012 422, 1674 Google Scholar

  • [8] M. Masias, M. Peracaula, J. Freixenet, X. Lladó: Exp. Astron., 2013, 36, 591 Google Scholar

  • [9] U. Moschini et al., Proceedings of the 2014 conference on Big Data from Space (BiDS’14), Nov. 12-14, 2014, Frascati, Italy (Publications Office of the European Union) 232 Google Scholar

  • [10] G. K. Ouzounis, M. H. F. Wilkinson, IEEE T. Pattern Anal., 2011, 33, 224 Google Scholar

  • [11] B. Perret, S. Lefevre, C. Collet, E. Slezak, Proceedings of International Conference on Pattern Recognition, Aug. 23-26, 2010, Istanbul, Turkey (IEEE) 4089 Google Scholar

  • [12] P. Salembier, A. Oliveras, L. Garrido, IEEE T. Image Process., 1998, 7, 555 Google Scholar

  • [13] sdss.org, 2007: Photometric flux calibration - published online: http://www.sdss2.org/dr7/algorithms/fluxcal.html Google Scholar

  • [14] J. Serra, Image Analysis and Mathematical Morphology, Part II: Theoretical Advances, 1988, Academic Press, London Google Scholar

  • [15] P. Serra et al., Mon. Not. R. Astron. Soc., 2015, 448, 2 Google Scholar

  • [16] C. Stoughton et al., Astron. J., 2002, 123, 1 (2002) Google Scholar

  • [17] P. Teeninga, U. Moschini, S. C. Trager, and M. H. F. Wilkinson, 11th International Conference Pattern Recognition and Image Analysis: New Information Technologies, Sep. 23-28, 2013, Samara, Russia (IPSI RAS) 746 Google Scholar

  • [18] P. Teeninga, U. Moschini, S. C. Trager, M. H. F. Wilkinson, Proceedings of International Conference on Image Processing, Sep. 27-30, 2015, Quebec City, Canada, (IEEE) Google Scholar

  • [19] N. Young, A. N. Evans, IEE P-Vis. Image Sign., 2003, 150, 5 Google Scholar

About the article

Received: 2015-07-09

Accepted: 2016-02-18

Published Online: 2016-03-30


Citation Information: Mathematical Morphology - Theory and Applications, ISSN (Online) 2353-3390, DOI: https://doi.org/10.1515/mathm-2016-0006.

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© 2016 Paul Teeninga et al.. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. BY-NC-ND 3.0

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