PARALLELIZATION AND ALGORITHMIC ENHANCEMENTS OF HIGH-RESOLUTION IRAS IMAGE CONSTRUCTION

The Infrared Astronomical Satellite carried out a nearly complete surv ey of the infrared sky, and the survey data are important for the stud y of many astrophysical phenomena. However, many data sets at other wa velengths have higher resolutions than that of the coadded IRAS maps, and high-resolution IRAS images are strongly desired both for their ow n information content and their usefulness in correlation studies. The HIRES program was developed by the Infrared Processing and Analysis C enter (IPAC) to produce high-resolution (similar to 1') images from IR AS data using the maximum correlation method (MCM). We describe the po rt of HIRES to the Intel Paragon, a massively parallel supercomputer, other software developments for mass production of HIRES images, and t he IRAS Galaxy Atlas, a project to map the Galactic plane at 60 and 10 0 mu m. Images produced from the MCM algorithm sometimes suffer from v isible striping and ringing artifacts. Correcting detector gain offset s and using a Burg entropy metric in the reconstruction scheme were fo und to be effective in suppressing these artifacts. A variation of the destriping algorithm was used to subtract zodiacal emission.