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Proceedings Paper

Fast algorithms for phase-diversity-based blind deconvolution
Author(s): Curtis R. Vogel; Tony F. Chan; Robert J. Plemmons
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Paper Abstract

Phase diversity is a technique for obtaining estimates of both the object and the phase, by exploiting the simultaneous collection of two short-exposure optical images, one of which has been formed by further blurring regularized variant of the Gauss-Newton optimization method for phase diversity-based estimated when a Gaussian likelihood fit-to-data criterion is applied. Simulation studies are provided to demonstrate that the method is remarkably robust and numerically efficient.

Paper Details

Date Published: 11 September 1998
PDF: 12 pages
Proc. SPIE 3353, Adaptive Optical System Technologies, (11 September 1998); doi: 10.1117/12.321720
Show Author Affiliations
Curtis R. Vogel, Montana State Univ. (United States)
Tony F. Chan, Univ. of California/Los Angeles (United States)
Robert J. Plemmons, Wake Forest Univ. (United States)

Published in SPIE Proceedings Vol. 3353:
Adaptive Optical System Technologies
Domenico Bonaccini; Robert K. Tyson, Editor(s)

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