Segmenting SAR Images Using Fuzzy Clustering

Abstract

Polarimetnc Synthetic Aperture Radar (SAR) Images have great potential for land use management provided the images can be efficiently segmented. Clustering is one segmentation technique currently being explored. This paper compares two different fuzzy clustering techniques on SAR images that minimize two different objective functions. Examples of both methods are presented and future efforts to improve both results discussed.

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Document Details

Document Type
Technical Report
Publication Date
Jul 02, 1999
Accession Number
ADA378143

Entities

People

  • Jim S. Verdi
  • Paul R. Kersten
  • Roger R. Lee
  • Ron M. Carvlho
  • Stephen P. Yankovich

Organizations

  • Naval Air Warfare Center

Tags

Communities of Interest

  • Air Platforms
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Abstracts
  • Aerial Warfare
  • Aircrafts
  • Algorithms
  • Clustering
  • Computer Vision
  • Computing-Related Activities
  • Data Sets
  • Detectors
  • Dynamic Range
  • Estimators
  • High Resolution
  • Iterations
  • Pattern Recognition
  • Radar
  • Segmented
  • Synthetic Aperture Radar

Fields of Study

  • Computer science

Readers

  • Computer Vision.
  • Systems Analysis and Design