High Resolution Image Construction from IRAS Survey — Parallelization and Artifact Suppression

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.

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