Image Segmentation Using Affine Wavelets

Abstract

This thesis discusses the use of the multiresolution representation and Radial Basis Function (RBF) neural networks to segment both FLIR and SAR imagery. The multiresolution approximation coefficients are used as features into the RBF network which learns to distinguish between different cultural and natural regions or objects. The wavelets used are Mallat's spline wavelet and Daubechies' compactly supported wavelets. Additionally, this thesis provides an explanation of wavelets in a tutorial manner. It introduces wavelet theory and discusses two different approaches to generating the multiresolution or wavelet representation.

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Document Details

Document Type
Technical Report
Publication Date
Dec 12, 1991
Accession Number
ADA243918

Entities

People

  • Steven E. Smiley

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force
  • Computer Programming
  • Computer Programs
  • Computer Vision
  • Electrical Engineering
  • Feature Extraction
  • Gray Scale
  • Image Processing
  • Image Segmentation
  • Machine Learning
  • Pattern Recognition
  • Processing Equipment
  • Recognition
  • Synthetic Aperture Radar
  • Target Recognition
  • Two Dimensional
  • United States

Readers

  • Computer Vision.
  • Image Processing and Computer Vision.
  • Neural Network Machine Learning.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Neural Networks