Comparison of various image fusion methods for impervious surface classification from VNREDSat-1

Impervious surface is an important indicator for urban development monitoring. Accurate urban impervious surfaces mapping with VNREDSat-1 remains challenging due to their spectral diversity not captured by individual PAN image. In this artical, five multi-resolution image fusion techniques were comp...

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Bibliographic Details
Published inarXiv.org
Main Authors Luu, Hung V, Pham, Manh V, Man, Chuc D, Bui, Hung Q, Nguyen, Thanh T N
Format Paper
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 04.05.2018
Subjects
Computer vision
Flood control
Image classification
Image processing
Mapping
Urban development
Wavelet analysis
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Summary:Impervious surface is an important indicator for urban development monitoring. Accurate urban impervious surfaces mapping with VNREDSat-1 remains challenging due to their spectral diversity not captured by individual PAN image. In this artical, five multi-resolution image fusion techniques were compared for classification task of urban impervious surface. The result shows that for VNREDSat-1 dataset, UNB and Wavelet tranform methods are the best techniques reserving spatial and spectral information of original MS image, respectively. However, the UNB technique gives best results when it comes to impervious surface classification especially in the case of shadow area included in non-impervious surface group.
ISSN:2331-8422