Astrometry.net: Blind astrometric calibration of arbitrary astronomical images

Dustin Lang, David W. Hogg, Keir Mierle, Michael Blanton, Sam Roweis

    Research output: Contribution to journalArticle

    Abstract

    We have built a reliable and robust system that takes as input an astronomical image, and returns as output the pointing, scale, and orientation of that image (the astrometric calibration or World Coordinate System information). The system requires no first guess, and works with the information in the image pixels alone; that is, the problem is a generalization of the "lost in space" problem in which nothing - not even the image scale - is known. After robust source detection is performed in the input image, asterisms (sets of four or five stars) are geometrically hashed and compared to pre-indexed hashes to generate hypotheses about the astrometric calibration. A hypothesis is only accepted as true if it passes a Bayesian decision theory test against a null hypothesis. With indices built from the USNO-B catalog and designed for uniformity of coverage and redundancy, the success rate is >99.9% for contemporary near-ultraviolet and visual imaging survey data, with no false positives. The failure rate is consistent with the incompleteness of the USNO-B catalog; augmentation with indices built from the Two Micron All Sky Survey catalog brings the completeness to 100% with no false positives. We are using this system to generate consistent and standards-compliant meta-data for digital and digitized imaging from plate repositories, automated observatories, individual scientific investigators, and hobbyists. This is the first step in a program of making it possible to trust calibration meta-data for astronomical data of arbitrary provenance.

    Original languageEnglish (US)
    Pages (from-to)1782-1800
    Number of pages19
    JournalAstronomical Journal
    Volume139
    Issue number5
    DOIs
    StatePublished - Apr 22 2010

    Keywords

    • Astrometry
    • Catalogs
    • Instrumentation: miscellaneous
    • Methods: data analysis
    • Methods: statistical
    • Techniques: image processing

    ASJC Scopus subject areas

    • Astronomy and Astrophysics
    • Space and Planetary Science

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