Segmentation of Synthetic Aperture Radar (SAR) Images of Ocean Surface by the Texture Energy Transform Method

Abstract

A texture energy transform approach has been chosen for the study of texture analysis and classification in digital images. It is based on the idea of detecting the degree of similarity between the spatial variation of image pixels and a set of chosen mask filters. Feature measures which characterize the texture are simpler to compute as compared with other approaches based on auto- correlation functions, digital transform methods, spatial gray tone co- occurrence probabilities, auto-regression models, etc. An algorithm was developed for the segmentation of SAR ocean surface images into regions with and without directional streaks. Excellent results are obtained in which surface areas with relatively rough and calm water are identified.

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Document Details

Document Type
Technical Report
Publication Date
Aug 17, 1988
Accession Number
ADA199536

Entities

People

  • Li-jen Du

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Air Platforms

DTIC Thesaurus Topics

  • Aerial Photographs
  • Algorithms
  • Classification
  • Computations
  • Computer Vision
  • Convolution
  • Detectors
  • Discriminant Analysis
  • Frequency Domain
  • Identification
  • Image Segmentation
  • Images
  • Information Science
  • Military Research
  • Radar
  • Statistics
  • Synthetic Aperture Radar

Fields of Study

  • Physics

Readers

  • Neural Network Machine Learning.
  • Radar Systems Engineering.
  • Vision Science/Vision Psychology/Cognitive Neuroscience.