A Fast and Optimal Multi-Frame Blind Deconvolution Algorithm for High-Resolution Ground-Based Imaging of Space Objects--Journal Article (Preprint)

Abstract

We report on a multi-frame 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-peformance computer, 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 the quality of its output to the associated Crammer-Rao lower bounds and demonstrated that, for the cases we have tested, it achieves or closely approaches these bounds. In this paper, we describe the algorithm and its parallelization in detail, demonstrate the scalability of its parallelization across associated Crammer-Rao lower bounds, and present image restorations obtained using data collected with ground-based telescopes.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 2008
Accession Number
ADA487957

Entities

People

  • Charles C. Beckner Jr.
  • Charles L. Matson
  • E. K. Hege
  • Kathy Borelli
  • Michael Lloyd-hart
  • Stuart Jefferies

Organizations

  • Air Force Research Laboratory

Tags

DTIC Thesaurus Topics

  • Air Force
  • Air Force Facilities
  • Air Force Research Laboratories
  • Algorithms
  • Department Of Defense
  • Directed Energy Weapons
  • Governments
  • Ground Based
  • High Resolution
  • Image Restoration
  • Information Operations
  • Military Research
  • Space Objects

Fields of Study

  • Engineering

Readers

  • Image Processing and Computer Vision.
  • Operations Research
  • Parallel and Distributed Computing.

Technology Areas

  • Space
  • Space - Space Objects