Feature extraction of hyperspectral data using the best wavelet packet basis

Pai Hui Hsu, Yi Hsing Tseng

Research output: Contribution to conferencePaper

8 Citations (Scopus)

Abstract

An adaptive wavelet decomposition algorithm called the Best Wavelet Packet Basis is used to extract the most useful spectral features from the original hyperspectral data for classification applications. Tested on a set of AVIRIS data, the novel feature extraction method is evaluated and compared with some contemporary feature extraction methods.

Original languageEnglish
Pages1667-1669
Number of pages3
Publication statusPublished - 2002 Jan 1
Event2002 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2002) - Toronto, Ont., Canada
Duration: 2002 Jun 242002 Jun 28

Other

Other2002 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2002)
CountryCanada
CityToronto, Ont.
Period02-06-2402-06-28

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Earth and Planetary Sciences(all)

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    Hsu, P. H., & Tseng, Y. H. (2002). Feature extraction of hyperspectral data using the best wavelet packet basis. 1667-1669. Paper presented at 2002 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2002), Toronto, Ont., Canada.