Abstract

This work presents methods for multispectral image classification using the discrete wavelet transform. Performance of some conventional classification methods is evaluated, through a Monte Carlo Study, with or without using the wavelet transform. Spatial autocorrelation is present in the computer-generated data on different scenes, and the misclassification rates are compared. The results indicate that the wavelet-based method performs best among the methods under study. (C) 2002 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved

Keywords

Contextual classification; wavelet; spatial autocorrelation; multispectral imagery; Monte Carlo study; Remote sensing

Published in

Pattern Recognition
2003, Volume: 36, number: 4, pages: 889-898
Publisher: PERGAMON-ELSEVIER SCIENCE LTD

SLU Authors

• Yu, Jun

  • Department of Forest Economics, Swedish University of Agricultural Sciences
    

• Ekström, Magnus

  • Department of Forest Economics, Swedish University of Agricultural Sciences
    

Publication identifier

DOI: https://doi.org/10.1016/S0031-3203(02)00125-5

Permanent link to this page (URI)

https://res.slu.se/id/publ/4983