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Multispectral image classification using wavelets: a simulation study
Centre of Biostochastics, Swedish University of Agricultural Sciences, Umeå, Sweden.
Centre of Biostochastics, Swedish University of Agricultural Sciences, Umeå, Sweden.
2003 (English)In: Pattern Recognition, ISSN 0031-3203, E-ISSN 1873-5142, Vol. 36, no 4, 889-898 p.Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Elsevier, 2003. Vol. 36, no 4, 889-898 p.
Keyword [en]
Contextual classification, wavelet, spatial autocorrelation, multispectral imagery, Monte Carlo study, remote sensing
National Category
Probability Theory and Statistics
Research subject
Mathematical Statistics
Identifiers
URN: urn:nbn:se:umu:diva-63693DOI: 10.1016/S0031-3203(02)00125-5ISI: 000180577600004OAI: oai:DiVA.org:umu-63693DiVA: diva2:582363
Available from: 2013-01-04 Created: 2013-01-04 Last updated: 2017-12-06Bibliographically approved

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Yu, JunEkström, Magnus
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