Selection of feature variables in spatial discrimination of remotely-sensed satellite imagery

Ryuei Nishii

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Statistical discriminant procedures based on multi-spectral images are widely used for land-cover classification. However, all images available for discrimination are not always useful for discrimination. In this article we consider a spatially-correlated multivariate normal distribution for the multispectral data. Under the local continuity of land-cover categories, we propose a statistical techniques for finding the best and parsimonious subset of the multispectral feature variables.

Original languageEnglish
Title of host publicationInternational Geoscience and Remote Sensing Symposium (IGARSS)
PublisherIEEE
Pages1813-1815
Number of pages3
Volume3
Publication statusPublished - 1999
Externally publishedYes
EventProceedings of the 1999 IEEE International Geoscience and Remote Sensing Symposium (IGARSS'99) 'Remote Sensing of the Systems Earth - A Challenge for the 21st Century' - Hamburg, Ger
Duration: Jun 28 1999Jul 2 1999

Other

OtherProceedings of the 1999 IEEE International Geoscience and Remote Sensing Symposium (IGARSS'99) 'Remote Sensing of the Systems Earth - A Challenge for the 21st Century'
CityHamburg, Ger
Period6/28/997/2/99

All Science Journal Classification (ASJC) codes

  • Software
  • Geology

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