Iterative/Recursive Deconvolution with Application to HST Data

James M. Coggins Laura Kellar Fullton and Bruce W. Carney

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.

Pages 24-39

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