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, E. Keith Hege, Lloyd Hart Michael

Research output: Contribution to journalArticle

52 Scopus citations

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 Cramer-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 Cramer-Rao lower bounds, and present image restorations obtained by using data collected with ground-based telescopes.

Original languageEnglish (US)
Pages (from-to)A75-A92
JournalApplied optics
Volume48
Issue number1
DOIs
StatePublished - Jan 1 2009

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Engineering (miscellaneous)
  • Electrical and Electronic Engineering

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