Image Correlation. Part II. Theoretical Basis.

Abstract

The fundamental nature of the map-matching problem is examined and theoretical justification for using various comparison metrics is investigated. Since the problem is one of statistical decision theory, the optimum solution is to compute the likelihood ratio for each comparison and choose the match point at a place where the likelihood ratio is maximum. That requires a knowledge of N-dimensional joint probability distributions, hence, we resort to approximations that maximize or minimize several functions called 'metrics'. By considering two-picture-element scenes, the features of various metrics are explained and compared with the likelihood ratio. In this way heuristic arguments are developed that support the use of the Product algorithm (a sum of products that is related to classical correlation) when S/N is low, and the MAD algorithm (mean absolute difference) when S/N is high. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1976
Accession Number
ADA036482

Entities

People

  • H. W. Wessely

Organizations

  • RAND Corporation

Tags

Communities of Interest

  • Sensors
  • Weapons Technologies

DTIC Thesaurus Topics

  • Acquisition
  • Air Force
  • Algorithms
  • Decision Theory
  • Detection
  • Detectors
  • Gaussian Distributions
  • Guidance
  • Probability
  • Probability Density Functions
  • Probability Distributions
  • Random Variables
  • Signal Detection
  • Simulations
  • Statistical Decision Theory
  • Statistics
  • Terminal Guidance

Readers

  • Computer Vision.
  • Materials Science and Engineering.
  • Statistical inference.