A Comparison of Multi-Frame Blind Deconvolution and Speckle Imaging Energy Spectrum Signal-to-Noise Ratios (Preprint)

Abstract

An analytical signal-to-noise ratio (SNR) expression is derived for unbiased estimates of energy spectra obtained using multi-frame blind deconvolution (MFBD) algorithms. Because an analytical variance expression cannot, in general, be derived, Cramer-Rao lower bounds are used in place of the variances. As a result, the SNR expression provides upper bounds to the achievable SNRs that are independent of the MFBD algorithm implementation. The SNR expression is evaluated for the scenario of ground-based imaging of astronomical objects. It is shown that MFBD energy-spectrum SNRs are usually greater, and often much greater, than their corresponding speckle imaging (SI) energy-spectrum SNRs at all spatial frequencies. One reason for this SNR disparity is that SI energy spectrum SNRs are proportional to the object energy spectrum and the ensemble-averaged atmosphere energy spectrum, while MFBD SNRs are approximately proportional to the square root of these quantities. Another reason for this SNR disparity is that single-frame SI energy spectrum SNRs are limited above by one, while the MFBD energy-spectrum SNRs are not.

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Document Details

Document Type
Technical Report
Publication Date
Sep 11, 2008
Accession Number
ADA487955

Entities

People

  • Charles L. Matson

Organizations

  • Air Force Research Laboratory

Tags

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Algorithms
  • Atmospheres
  • Atmospheric Motion
  • Directed Energy Weapons
  • Frequency
  • Image Reconstruction
  • Intensity
  • Low Light Levels
  • Measurement
  • Military Research
  • Numbers
  • Photons
  • Spearography
  • Square Roots
  • Transfer Functions

Fields of Study

  • Engineering
  • Physics

Readers

  • Image Processing and Computer Vision.
  • Statistical inference.