Use of Hierarchical Stepwise Optimization for the Segmentation of Cloud Features

Abstract

The Hierarchical Stepwise Optimization algorithm of Beaulieu and Goldberg (1989) is applied to the segmentation of satellite images into meaningful, large scale cloud features. GOES-W visible imagery is used. Several different forms of the cost function are explored in an attempt to improve the segmentation of Nov. 15, 1983 case. A new cost function is shown to result in a superior segmentation. Both HSWO versions are tested on six additional cases. A modification to the HSWO approach is suggested for further research.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1991
Accession Number
ADA238987

Entities

People

  • J. E. Peak

Organizations

  • Computer Sciences Corporation

Tags

Communities of Interest

  • Space

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Artificial Intelligence
  • Artificial Intelligence Computing
  • Artificial Intelligence Software
  • Artificial Satellites
  • Bering Sea
  • Computer Science
  • Computer Vision
  • Computers
  • Data Sets
  • Expert Systems
  • Image Segmentation
  • Neural Networks
  • Optimization
  • Pattern Recognition
  • Tropical Cyclones

Readers

  • Atmospheric Remote Sensing.
  • Computer Vision.
  • Operations Research

Technology Areas

  • Space