Gabor Segmentation of High Resolution Synthetic Aperture Radar Imagery

Abstract

This thesis investigates the use of Gabor filters and a radial basis function (RBF) network for segmentation of high resolution (1 foot by 1 foot) synthetic aperture radar (SAR) imagery. Processing involved correlation between the SAR imagery and Gabor functions. Two methods for selecting the optimal Gabor filters are presented. This research used complex Gabor functions and operated on single polarization HH complex data. Following the selection f the proper Gabor filters, correlation coefficients for each image were calculated and used as features for the RBF network. Provided are results demonstrating how Gabor processing and a RBF network provide image segmentation.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1991
Accession Number
ADA243753

Entities

People

  • Michael A. Hazlett

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Sensors
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Artificial Intelligence
  • Classification
  • Corner Reflectors
  • Electrical Engineering
  • Frequency Response
  • High Resolution
  • Image Processing
  • Image Segmentation
  • Mechanical Jamming
  • Neural Networks
  • Pattern Recognition
  • Power Spectra
  • Recognition
  • Synthetic Aperture Radar
  • Target Recognition
  • Two Dimensional

Readers

  • Atmospheric Remote Sensing.
  • Maritime Security/Maritime Homeland Security
  • Neural Network Machine Learning.