Comparative Results With Massively Parallel Spatially - VariantMaximum Likelihood Image

Abstract

We present results of concurrent maximum likelihood restoration implementations with spatially-variant point spread function (SV-PSF), exhibiting performance superior to restoration with invariant PSF. We realize concurrency on a network of Unix workstations, and a SV-PSF model from sparse PSF reference information by means of bilinear interpolation. We then use the inter-polative PSF model to implement several diierent SV-PSF restoration methods. These restoration methods are tested on a standard Hubble Space Telescope test case, and the results are compared on a computational eeort/restoration performance basis.

Cite this paper

@inproceedings{Boden2007ComparativeRW, title={Comparative Results With Massively Parallel Spatially - VariantMaximum Likelihood Image}, author={Franz Boden and Robert J. Hanisch and Jixue Mo}, year={2007} }