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Iterative/Recursive Deconvolution with Application to HST Data

Next: Introduction

Iterative/Recursive Deconvolution with Application to HST Data

James M. Coggins

Department of Computer Science, CB 3175 Sitterson Hall, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-3175

Laura Kellar Fullton and Bruce W. Carney

Department of Physics and Astronomy, CB 3255 Phillips Hall, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-3255

Abstract:

A new deblurring algorithm has been developed involving both iteration and recursion and that is linear, flux-conserving, noise resistant, and faster to converge than extant iterative deblurring methods. Mathematical analysis shows that the recursive component of the algorithm provides the accelerated convergence. A demonstration is provided using a simulated star field image blurred using an approximation to the point spread function of the Hubble Space Telescope.

Keywords: iterative deconvolution, recursion, linear, flux-conserving, noise-resistant

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Thu Jun 2 16:01:49 EDT 1994