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Applied Optics

Applied Optics


  • Editor: Joseph N. Mait
  • Vol. 48, Iss. 1 — Jan. 1, 2009
  • pp: A75–A92

Fast and optimal multiframe blind deconvolution algorithm for high-resolution ground-based imaging of space objects

Charles L. Matson, Kathy Borelli, Stuart Jefferies, Charles C. Beckner, Jr., E. Keith Hege, and Michael Lloyd-Hart  »View Author Affiliations

Applied Optics, Vol. 48, Issue 1, pp. A75-A92 (2009)

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We report a multiframe blind deconvolution algorithm that we have developed for imaging through the atmosphere. The algorithm has been parallelized to a significant degree for execution on high- performance computers, with an emphasis on distributed-memory systems so that it can be hosted on commodity clusters. As a result, image restorations can be obtained in seconds to minutes. We have compared and quantified the quality of its image restorations relative to the associated Cramér–Rao lower bounds (when they can be calculated). We describe the algorithm and its parallelization in detail, demonstrate the scalability of its parallelization across distributed-memory computer nodes, discuss the results of comparing sample variances of its output to the associated Cramér–Rao lower bounds, and present image restorations obtained by using data collected with ground-based telescopes.

© 2008 Optical Society of America

OCIS Codes
(100.3020) Image processing : Image reconstruction-restoration
(100.1455) Image processing : Blind deconvolution
(110.3055) Imaging systems : Information theoretical analysis
(110.4155) Imaging systems : Multiframe image processing

Original Manuscript: April 25, 2008
Revised Manuscript: October 15, 2008
Manuscript Accepted: October 21, 2008
Published: December 4, 2008

Charles L. Matson, Kathy Borelli, Stuart Jefferies, Charles C. Beckner, Jr., E. Keith Hege, and Michael Lloyd-Hart, "Fast and optimal multiframe blind deconvolution algorithm for high-resolution ground-based imaging of space objects," Appl. Opt. 48, A75-A92 (2009)

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