Texture Classification Using Wavelet Packet and Fourier Transforms.

Abstract

A new texture classification algorithm using wavelet packet transform is proposed. It uses principal component analysis technique and statistical distance measurement to combine and select frequency channel features to give improved classification performance. Comparison is also made between wavelet packet transform features and Fourier transform features on a set of eight optical texture images with several level of white noise added. Both algorithms are successfully applied to the classification of under-ice sidescan sonar images.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1995
Accession Number
ADA324161

Entities

People

  • W. K. Stewart
  • Xiaoou Tang

Organizations

  • Woods Hole Oceanographic Institution

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Computer Vision
  • Data Sets
  • Databases
  • Ecology
  • Equations
  • Factor Analysis
  • Feature Selection
  • Frequency
  • Frequency Bands
  • Image Processing
  • Images
  • Information Science
  • Optical Images
  • Sonar Images
  • Two Dimensional
  • Wavelet Transforms

Fields of Study

  • Engineering

Readers

  • Acoustical Oceanography.
  • Computer Vision.
  • Image Processing and Computer Vision.