Paper:	Massively Parallel Spatially-Variant Maximum Likelihood Image Restoration
Volume:	101, Astronomical Data Analysis Software and Systems V
Page:	131
Authors:	Boden, A. F.; Redding, D. C.; Hanisch, R. J.; Mo, J.
Abstract:	Motivated by attributes of images from the Hubble Space Telescope (HST) Wide Field/Planetary Cameras (WF/PC-1 and WFPC-2), in this paper we report on massively parallel implementations of maximum likelihood image restoration with spatially-variant point-spread (SV-PSF) models. We use an interpolative procedure to realize a SV-PSF model from sparse reference data, and realize the large amount of concurrency inherent in the restoration computation by employing a Trussel & Hunt-style segmentation of the restoration task, distributing the work load on a network of UNIX workstations using the public domain PVM system. We give examples of application of the restoration code to recent WFPC2 observations of HH 47.

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