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Title
Mapping 'Lantana camara': Accuracy Comparison of Various Fusion Techniques
Fields of Research (FoR) 2008:
Author(s)
Publication Date
2010
Socio-Economic Objective (SEO) 2008
Abstract
Fusion of panchromatic and multi-spectral QuickBird satellite imagery was carried out to evaluate the impact of fusion techniques on classification accuracies for Lantana mapping. This study compared four image fusion techniques, namely Brovey, Hue-Saturation-Value, Principal Components, and Gram-Schmidt Spectral Sharpening. Classification accuracy assessment was calculated using an error matrix for all images. Gram-Schmidt and Principal Components spectral sharpening techniques had an overall accuracy of 90.5 percent and 89.5 percent and a kappa coefficient of 0.85 and 0.84, respectively, compared to the MS image which had an overall accuracy of 86.3 percent and a kappa coefficient of 0.79. Brovey transformation and HSV performed poorly in the supervised classification with overall accuracies of 64.2 percent and 76.8 percent and kappa coefficients of 0.48 and 0.65, respectively. Visual and statistical analyses of the fused images showed that Gram-Schmidt and Principal Components spectral sharpening techniques preserved spectral quality much better than the Brovey and HSV fused images.
Publication Type
Journal Article
Source of Publication
Photogrammetric Engineering and Remote Sensing, 76(6), p. 691-700
Publisher
American Society for Photogrammetry and Remote Sensing
Place of Publication
United States of America
ISSN
0099-1112
Peer Reviewed
Yes
HERDC Category Description
Peer Reviewed
Yes
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