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Blind Deconvolution of HST Simulated Data

Julian C. Christou

Starfire Optical Range, Phillips Laboratory, PL/LIG, Kirtland AFB, NM 87117

Stuart M. Jefferies

Bartol Research Institute, University of Delaware, Newark, DE 19716

Mark W. Robison

School of Physics &Astronomy, University of Minnesota, Minneapolis, MN 55455

[1]Steward Observatory, University of Arizona, Tucson, AZ 85721 [2]Visiting Astronomer, National Solar Observatory, Tucson, AZ 85726. NSO is operated by AURA, Inc. under contract to the National Science Foundation. [3]Summer Research Student, National Solar Observatory, Tucson, AZ 85726.

Abstract:

We apply an iterative deconvolution algorithm, which has the capability to recover both the object and point spread function from a single image or multiple images, to simulated HST star cluster data. The algorithm uses error metric minimization to enforce known physical constraints on both the reconstructed object and point spread function. The reconstructed object is shown to preserve the photometry inherent in the observed image. The use of multiple observations improves the signal-to-noise ratio of the reconstructed object.

Keywords: blind deconvolution, image processing

rlw@sundog.stsci.edu
Mon Apr 18 14:59:01 EDT 1994