Segmentation of Multilook, Multifrequency, and Multipolarimetric SAR Data.

Abstract

This final report summarizes the findings of the research, "Segmentation of Multi-look, Multi-frequency and Multi-polarimetric SARt data." During the duration of the project, we have developed algorithms for (a) Markov Random Field based segmentation of high resolution SAR images, (b) detection of man-made features in SAR images and (c) labeling, as well as, grouping algorithms. These algorithms have been integrated to produce a 2-D site model of the given SAR image. The 2-D site model is an annotated description of the SAR image incorporating natural and man-made features such as trees, grass, water, open terrain, buildings, roads and shadows. Such site models are useful for delineating regions of interest (which serve as focus of attention mechanisms) and for providing local context in ATR algorithms.

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Document Details

Document Type
Technical Report
Publication Date
Nov 20, 1995
Accession Number
ADA303538

Entities

People

  • Rama Chellappa

Organizations

  • University of Maryland

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Cells
  • Computer Vision
  • Detection
  • Detectors
  • Electrical Engineering
  • False Alarms
  • High Resolution
  • Image Processing
  • Probability
  • Random Variables
  • Synthetic Aperture Radar
  • Target Detection
  • Target Recognition
  • Two Dimensional
  • Warning Systems

Readers

  • Computer Vision.
  • Radar Systems Engineering.