Skip to main content
SLU publication database (SLUpub)

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

UKÄ Subject classification

Probability Theory and Statistics

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