Abstract

A brief introduction to image reconstruction is made and the basic concepts of the maximum entropy method are outlined. A statistical inference algorithm based on this method is presented. The algorithm is tested on simulated data and applied to real data. The latter is from a 1024 × 1024 Hubble Space Telescope image of the binary stellar system R Aquarii, which suffers from both spherical aberration and detector saturation. Under these constraints the maximum entropy method produces an image that agrees closely with observed results. The calculations were performed on the MasPar MP-1 single-instruction/multiple-data computer.

© 1993 Optical Society of America

Massively parallel spatially variant maximum-likelihood restoration of Hubble Space Telescope imagery

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