Polar shapelets
- Creators
- Massey, Richard
- Refregier, Alexandre
Abstract
The shapelets method for image analysis is based upon the decomposition of localized objects into a series of orthogonal components with convenient mathematical properties. We extend the 'Cartesian shapelet' formalism from earlier work, and construct 'polar shapelet' basis functions that separate an image into components with explicit rotational symmetries. These frequently provide a more compact parametrization, and can be interpreted in an intuitive way. Image manipulation in shapelet space is simplified by the concise expressions for linear coordinate transformations, and shape measures (including object photometry, astrometry and galaxy morphology estimators) take a naturally elegant form. Particular attention is paid to the analysis of astronomical survey images, and we test shapelet techniques upon real data from the Hubble Space Telescope. We present a practical method to automatically optimize the quality of an arbitrary shapelet decomposition in the presence of observational noise, pixelization and a point spread function. A central component of this procedure is the adaptive choice of the scale size and the truncation order of the shapelet expansion. A complete software package to perform shapelet image analysis is made available on the World Wide Web.
Additional Information
©2005 RAS. This paper has been typeset from a TEX/LATEX file prepared by the author. Accepted 2005 July 13. Received 2005 July 6; in original form 2004 August 25 The authors thank David Bacon, Gary Bernstein, Sarah Bridle, Tzu-Ching Chang, Mark Coffey, Chris Conselice, Phil Marshall and Jean-Luc Starck for invaluable insights and constructive conversations. Astute suggestions from the referee helped shape this paper into a more logical progression.Files
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Additional details
- Eprint ID
- 6358
- Resolver ID
- CaltechAUTHORS:MASmnras05
- Created
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2006-12-05Created from EPrint's datestamp field
- Updated
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2021-11-08Created from EPrint's last_modified field