Improving Classification Accuracy of Radar Images Using a Multiple-Stage Classifier

Abstract

A simple method was introduced to classify radar image samples repeatedly for achieving a higher accuracy than by using a single-stage classifier. A Sobel edge operator was applied between the stages of classification to enhance the difference in texture between categories of radar image samples, thus reducing the overlap of image categories. Keywords: Radar image feature extraction; Texture; Histogram; Classification; Pattern recognition; and Edge operators.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1988
Accession Number
ADA200291

Entities

People

  • Neil D. Fox
  • Pi-fuay Chen

Organizations

  • Geospatial Research Laboratory

Tags

Communities of Interest

  • Space

DTIC Thesaurus Topics

  • Accuracy
  • Engineers
  • Extraction
  • Feature Extraction
  • High Resolution
  • Identification
  • Machine Learning
  • Measurement
  • Pattern Recognition
  • Probability
  • Probability Distributions
  • Radar
  • Radar Images
  • Recognition
  • Security
  • Synthetic Aperture Radar
  • Virginia

Readers

  • Computer Vision.
  • Regression Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks