Minimum distance texture classification of SAR images using wavelet packets

N D Fletcher, Adrian N Evans

Research output: Contribution to conferencePaperpeer-review

3 Citations (SciVal)

Abstract

A multi-scale texture segmentation algorithm for SAR images based on the discrete wavelet transform is presented. Responses from different sub-bands are used to form a feature vector for each pixel position that is the input to the classification scheme. To further improve the classification results, the tree-structured wavelet packet transform is used to automatically identify a suitable sub-set of elements from the feature vector. Results show that this approach is effective for both the redundant and non-redundant wavelet transforms.
Original languageEnglish
PagesIII-1438-III-1440
DOIs
Publication statusPublished - 24 Jun 2002
EventIEEE International Geoscience and Remote Sensing Symposium (IGARSS '02) - Toronto, Canada
Duration: 24 Jun 200228 Jun 2002

Conference

ConferenceIEEE International Geoscience and Remote Sensing Symposium (IGARSS '02)
Country/TerritoryCanada
CityToronto
Period24/06/0228/06/02

Keywords

  • Geophysical signal processing
  • Image texture
  • Radar imaging
  • Feature vector
  • Multi-scale texture segmentation algorithm
  • Image segmentation
  • Remote sensing by radar
  • Redundant wavelet transforms
  • SAR images
  • Discrete wavelet transforms
  • Minimum distance texture classification
  • Synthetic aperture radar
  • Sub-bands tree-structured wavelet packet transform
  • Image classification
  • Discrete wavelet transform
  • Wavelet packet
  • Nonredundant wavelet transforms

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