Wavelet Analysis for RADARSAT Exploitation: Demonstration of Algorithms for Maritime Surveillance

Abstract

This document reports on Wavelet Analysis for RADARSAT Exploitation (WARE), research software that aims to demonstrate the applications of wavelet analysis to RADARSAT ocean imagery. Wavelets are a mathematical paradigm that can be used to partition data into various frequency components, allowing the study of each component at a resolution matched to its scale. Wavelets are an efficient image processing tool for localized feature extraction and texture analysis. WARE tools have been developed using basic wavelet-based algorithms and include: (a) wind direction estimation; (b) oceanic or atmospheric front extraction; (c) oil spill detection; and (d) ship detection. WARE includes rudimentary interactive validation and has been applied to several RADARSAT ocean images that span the noted application areas. As such, the distinctive properties and advantages of wavelet analysis for target detection and recognition are demonstrated. In future, WARE could be extended to include radiometric flattening, improved algorithm efficiencies in anticipation of operationalization, and systematic testing of available wavelet families for improved algorithm performance.

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 2007
Accession Number
ADA640085

Entities

People

  • John Wolfe
  • Paris W. Vachon
  • Yong Du

Organizations

  • Defence Research and Development Canada

Tags

Communities of Interest

  • Ground and Sea Platforms
  • Materials and Manufacturing Processes
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Algorithms
  • Bayesian Networks
  • Detection
  • Detectors
  • Dimensionality Reduction
  • Electromagnetic Radiation
  • Feature Extraction
  • Frequency
  • Graphical User Interface
  • Image Processing
  • Oil Spills
  • Radar
  • Supervised Machine Learning
  • Synthetic Aperture Radar
  • Target Detection
  • Unsupervised Machine Learning
  • Wind Direction

Readers

  • Image Processing and Computer Vision.
  • Marksmanship and Weaponry.
  • Software Engineering.

Technology Areas

  • AI & ML