Pattern Classification Techniques Applied to High Resolution, Synthetic Aperture Radar Imagery,

Abstract

This report describes the application of 10 pattern classification techniques to selected samples of high resolution, synthetic aperture radar imagery taken over the Huntsville, Alabama area. Sections of the radar imagery were digitized and stored on a digital disk unit. A Lexidata system 3400 image processor and a Hewlett Packard 1000 computer were used to display the images on a cathode ray tube and to take 100 samples for each of four terrain classes from the imagery. The 400 image samples were then used as training sets to derive the 10 classifiers. Once the classifiers were derived, the training set data were then used as input to the classifiers to see how well each would do in classifying the original training sets.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1986
Accession Number
ADA183537

Entities

People

  • Pi-fuay Chen
  • Richard A. Hevenor

Organizations

  • Geospatial Research Laboratory

Tags

Communities of Interest

  • Human Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Artificial Intelligence
  • Cathode Ray Tubes
  • Computational Complexity
  • Computer Programs
  • Covariance
  • Feature Selection
  • High Resolution
  • Information Science
  • Machine Learning
  • Pattern Recognition
  • Probability
  • Radar
  • Recognition
  • Statistics
  • Synthetic Aperture Radar

Readers

  • Computer Science/Computer Engineering/Data Science/Digital Signal Processing.
  • Military/Explosive Ordnance Disposal (EOD) Technology
  • Radar Systems Engineering.