title: Fast and optimal multiframe blind deconvolution algorithm for high-resolution ground-based imaging of space objects.
abstract: 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.
authors.affiliation: Air Force Research Laboratory, 3550 Aberdeen Avenue SE, Kirtland Air Force Base, New Mexico 87117, USA. charles.matson@kirtland.af.mil
authors.forename: Charles L
authors.initials: CL
authors.lastname: Matson
authors.forename: Kathy
authors.initials: K
authors.lastname: Borelli
authors.forename: Stuart
authors.initials: S
authors.lastname: Jefferies
authors.forename: Charles C
authors.initials: CC
authors.lastname: Beckner
authors.forename: E Keith
authors.initials: EK
authors.lastname: Hege
authors.forename: Michael
authors.initials: M
authors.lastname: Lloyd-Hart