Abstract
The Infrared Astronomical Satellite carried out a nearly complete survey of the infrared sky, and the survey data are important for the study of many astrophysical phenomena. However, many data sets at other wavelengths have higher resolutions than that of the co-added IRAS maps, and high resolution IRAS images are strongly desired both for their own information content and their usefulness in correlation studies.
The HIRES program was developed by the Infrared Processing and Analysis Center (IPAC) to produce high resolution (~ 1′) images from IRAS data using the Maximum Correlation Method (MCM). In this paper, we describe the port of HIRES to the Intel Paragon, a massively parallel supercomputer. A speed increase of about 7 times is achieved with 16 processors and 5 times with 8 processors for a 1° × 1° field. Equivalently a 64 square degree field can be processed using 512 nodes, with a speedup factor of 320.
Images produced from the MCM algorithm sometimes suffer from visible striping and ringing artifacts. Correcting detector gain offsets and using a Burg entropy metric in the restoration scheme were found to be effective in suppressing these artifacts.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
H. H. Aumann, J. W. Fowler and M. Melnyk, “A Maximum Correlation Method for Image Construction of IRASSurvey Data,” Astronomical Journal, Vol. 99(5),pp: 1674–1681,1990.
C. A. Beichman, “The IRASView of the Galaxy and the Solar-System,” Annual Review of Astronomy and Astrophysics, Vol. 25,pp: 521–563,1987.
T. R. Bontekoe, D. J. M. Kester, S. D. Price, A. R. W. Dejonge and P. R. Wesselius,“Image Construction from the IRASSurvey,” Astronomical Journal Vol. 248(1) pp: 328–336,1991
T. R. Bontekoe, E. Koper and D. J. M. Kester, “Pyramid Maximum-Entropy Images of IRASSurvey Data,” Astronomy and Astrophysics, Vol. 284(3),pp: 1037–1053,1994.
J. W. Fowler and M. Melnyk, LAUNDR Software Design Specifications, IPAC, Caltech, 1990.
B. R. Frieden, “Estimating Occurrence Laws with Maximum Probability, and the Transition to Entropie Estimators,” in Maximum-Entropy and Bayesian Methods in Inverse Problems, eds. C. R. Smith and W. T. Grandy, Jr., pp: 133–170, D. Reidel Publishing Company, Dordrecht, Holland,1985.
E. T. Jaynes, “Monkeys, Kangaroos, and N,” in Maximum Entropy and Bayesian Methods in Applied Statistics, ed. J. H. Justice, pp: 26–58, Cambridge University Press,1986.
L. B. Lucy, “An Iterative Technique for the Rectification of Observed Distributions,” Astronomical Journal, Vol. 79,pp: 745–754,1974.
A. R. De Pierro, “Multiplicative Iterative Methods in Computed Tomography,” in Mathematical Methods in Tomography, eds. G. T. Herman, A. K. Louis and F. Natterer, pp: 167–186, Springer-Verlag,1991.
W. H. Richardson, “Bayesian-Based Iterative Method of Image Restoration,” Journal of the Optical Society of America, Vol. 62,pp: 55–59,1972.
B. T. Soifer, J. R. Houck and G. Neugebauer, “The IRASView of the Extragalactic Sky,” Annual Review of Astronomy and Astrophysics, Vol. 25,pp: 187–230,1987.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1996 Kluwer Academic Publishers
About this paper
Cite this paper
Cao, Y., Prince, T.A. (1996). High Resolution Image Construction from IRAS Survey — Parallelization and Artifact Suppression. In: Skilling, J., Sibisi, S. (eds) Maximum Entropy and Bayesian Methods. Fundamental Theories of Physics, vol 70. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-0107-0_10
Download citation
DOI: https://doi.org/10.1007/978-94-009-0107-0_10
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-010-6534-4
Online ISBN: 978-94-009-0107-0
eBook Packages: Springer Book Archive