Multispectral image classification using wavelets: a simulation study

Sammanfattning

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

Nyckelord

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

Publicerad i

Pattern Recognition
2003, volym: 36, nummer: 4, sidor: 889-898
Utgivare: PERGAMON-ELSEVIER SCIENCE LTD

SLU författare

• Yu, Jun

  • Institutionen för skogsekonomi, Sveriges lantbruksuniversitet
    

• Ekström, Magnus

  • Institutionen för skogsekonomi, Sveriges lantbruksuniversitet
    

Publikationens identifierare

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

Permanent länk till denna sida (URI)

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