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Automated morphological classification of galaxies using wavelet transform

Published online by Cambridge University Press:  13 April 2010

Didier Curty
Affiliation:
Observatório Nacional, Rio de Janeiro, Brazil email: [email protected]
François C. Cuisinier
Affiliation:
Observatório do Valongo, Universidade Federal do Rio de Janeiro, Brazil email: [email protected], [email protected]
Carlos R. Rabaça
Affiliation:
Observatório do Valongo, Universidade Federal do Rio de Janeiro, Brazil email: [email protected], [email protected]
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Abstract

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The wavelet transform acts to segregate objects in function of their size. We apply this method on images of galaxies to decompose them into coefficients representing only objects of the same size. The total fluxes of the wavelet coefficients describe the cumulative power spectrum of spatial frequencies. Based on this spectrum, we propose a new parameter to quantify the galaxy texture. As expected, it remains small and quite invariant for early-type galaxies, while it covers a large range and takes larger values for late-type galaxies. Combined with a second parameter, our determination of the texture is able to successfully separate galaxy types. By thresholding the wavelet coefficients, we detect luminous lumps. In irregular galaxies, their radial distribution seems to show a double peak. This could be the trace of a privileged radial distance of strong star formation regions.

Type
Poster Papers
Copyright
Copyright © International Astronomical Union 2010

References

York, D. G. et al. 2000, AJ, 120, 1579CrossRefGoogle Scholar
Fukugita, M. et al. 2007, AJ, 134, 579CrossRefGoogle Scholar
Doi, M., Fukugita, M., & Okamura, S. 1993, MNRAS 264, 832CrossRefGoogle Scholar
Abraham, R. G., Valdes, F., Yee, H. K., & van den Bergh, S. 1994, ApJ 432, 75CrossRefGoogle Scholar
Parodi, B. R. & Binggeli, B. 2003, A&A 398, 501Google Scholar