Journal
ASTRONOMICAL JOURNAL
Volume 139, Issue 5, Pages 1782-1800Publisher
IOP PUBLISHING LTD
DOI: 10.1088/0004-6256/139/5/1782
Keywords
astrometry; catalogs; instrumentation: miscellaneous; methods: data analysis; methods: statistical; techniques: image processing
Categories
Funding
- NSERC
- CRC
- National Aeronautics and Space Administration (NASA) [NAG5-11669, NNX08AJ48G]
- National Science Foundation [AST-0428465, AST-0908357]
- Alexander von Humboldt Foundation
- NASA Spitzer Space Telescope [30842, 50568]
- Alfred P. Sloan Foundation
- Participating Institutions
- National Science Foundation
- U.S. Department of Energy
- National Aeronautics and Space Administration
- Japanese Monbukagakusho
- Max Planck Society
- Higher Education Funding Council for England
- American Museum of Natural History
- Astrophysical Institute Potsdam
- University of Basel, University of Cambridge
- Case Western Reserve University
- University of Chicago
- Drexel University
- Fermilab
- Institute for Advanced Study
- Japan Participation Group
- Johns Hopkins University
- Joint Institute for Nuclear Astrophysics
- Kavli Institute for Particle Astrophysics and Cosmology
- Korean Scientist Group, the Chinese Academy of Sciences (LAMOST)
- Los Alamos National Laboratory
- Max-Planck-Institute for Astronomy (MPIA)
- Max-PlanckInstitute for Astrophysics (MPA)
- New Mexico State University
- Ohio State University
- University of Pittsburgh
- University of Portsmouth
- Princeton University
- United States Naval Observatory
- University of Washington
- Division Of Astronomical Sciences
- Direct For Mathematical & Physical Scien [0908357] Funding Source: National Science Foundation
Ask authors/readers for more resources
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.
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