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Conference Paper
Frontiers in Optics
Rochester, New York United States
October 10, 2006
ISBN: 1-55752-818-7
Computational Imaging IV (FWN)

A Cramér-Rao Lower Bound Analysis of Noise Reduction Limits in Blind Deconvolution for Zernike-Based Point-Spread-Function Estimation with the Use of a Support Constraint

Charles L. Matson and Alim Haji

http://dx.doi.org/10.1364/FIO.2006.FWN5


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Abstract

We show in an algorithm-independent way that Zernike-based blind deconvolution of atmospherically-blurred images produces higher quality estimates of an object and the blurring PSFs than does pixel-based PSF estimation.

© 2006 Optical Society of America

OCIS Codes
(100.0100) Image processing : Image processing
(100.2960) Image processing : Image analysis
(100.3190) Image processing : Inverse problems

Citation
C. L. Matson and A. Haji, "A Cramér-Rao Lower Bound Analysis of Noise Reduction Limits in Blind Deconvolution for Zernike-Based Point-Spread-Function Estimation with the Use of a Support Constraint," in Frontiers in Optics, OSA Technical Digest (CD) (Optical Society of America, 2006), paper FWN5.
http://www.opticsinfobase.org/abstract.cfm?URI=FiO-2006-FWN5


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