NUMERICAL RESTORATION OF OPTICAL OBJECTS OBSURED BY DIFFRACTION AND NOISE

Abstract

The problem considered is the restoration of incoherent optical objects which have been diffracted by an optical system and corrupted by detector and additive background noise. The approach in solving the problem is basically numerical and considers operating directly on the image and point spread function rather than the Fourier transform of these quantities. Special emphasis is placed on studying the effects of noise and the use of a priori information in the restoration process. Several 'optimum' estimates of the object intensity distribution are considered. Based substantially on statistics which have been verified in practice, the Baye's, maximum a posteriori, maximum likelihood and mean square error estimates of the object intensity distribution are obtained. These statistical estimates are compared mathematically and in many cases numerically to other non-statistical estimates formulated from control theory and dynamic programming. Extensive numerical results have been obtained for the restoration of various one-dimensional objects in the presence of noise. Two monochromatic 'point sources' in the presence of noise are shown to be resolved when separated by 1/5 of the Rayleigh criterion distance. Numerical results are also shown for the mean square error as a function of a priori information, the measuring scheme chosen, and diffraction.

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Document Details

Document Type
Technical Report
Publication Date
Dec 31, 1966
Accession Number
AD0649261

Entities

People

  • Craig K. Rushforth
  • Richard W. Harris

Organizations

  • Utah State University

Tags

Communities of Interest

  • Air Platforms
  • C4I
  • Ground and Sea Platforms
  • Materials and Manufacturing Processes
  • Space

DTIC Thesaurus Topics

  • Air Force
  • Applied Mathematics
  • Background Noise
  • Computational Science
  • Computer Programming
  • Computer Programs
  • Computers
  • Control Theory
  • Detection
  • Detectors
  • Dynamic Programming
  • Equations
  • Integral Equations
  • Probability
  • Random Variables
  • Statistics
  • Theorems

Fields of Study

  • Physics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Image Processing and Computer Vision.
  • Statistical inference.