Thematic labelling from hyperspectral remotely sensed imagery: trade-offs in image properties
Thematic labelling from hyperspectral remotely sensed imagery: trade-offs in image properties
The effect of spatial, spectral and noise degradations on the accuracy of two highly contrasting thematic labelling scenarios was investigated. The study used hyperspectral imagery of a site near Falmouth, UK, to assess the effect of the data degradations on the accuracy of supervised classification when the H-resolution scene model was applicable and on labelling when an L-resolution scene model was applicable and no ground data were available. In both scenarios, the spatial, spectral and noise degradations affected the accuracy of labelling. However, over the range of degradations investigated, the noise content of the data was consistently noted to be a major variable affecting the accuracy of labelling.
2337-2363
Foody, G.M.
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Sargent, I.M.
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Atkinson, P.M.
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Williams, J.
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2004
Foody, G.M.
06e50027-603d-4a5b-88f5-af2bb6235a37
Sargent, I.M.
ddb0a4aa-5790-4637-9ee3-62fa571b67ab
Atkinson, P.M.
aaaa51e4-a713-424f-92b0-0568b198f425
Williams, J.
2ab33bc3-4988-493b-9cd5-ac68d28385cb
Foody, G.M., Sargent, I.M., Atkinson, P.M. and Williams, J.
(2004)
Thematic labelling from hyperspectral remotely sensed imagery: trade-offs in image properties.
International Journal of Remote Sensing, 25 (12), .
(doi:10.1080/01431160310001654969).
Abstract
The effect of spatial, spectral and noise degradations on the accuracy of two highly contrasting thematic labelling scenarios was investigated. The study used hyperspectral imagery of a site near Falmouth, UK, to assess the effect of the data degradations on the accuracy of supervised classification when the H-resolution scene model was applicable and on labelling when an L-resolution scene model was applicable and no ground data were available. In both scenarios, the spatial, spectral and noise degradations affected the accuracy of labelling. However, over the range of degradations investigated, the noise content of the data was consistently noted to be a major variable affecting the accuracy of labelling.
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Published date: 2004
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Local EPrints ID: 15442
URI: http://eprints.soton.ac.uk/id/eprint/15442
ISSN: 0143-1161
PURE UUID: 1eb60520-f4bf-46c8-9d78-a51862f0047b
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Date deposited: 19 Apr 2005
Last modified: 15 Mar 2024 05:39
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Author:
G.M. Foody
Author:
I.M. Sargent
Author:
P.M. Atkinson
Author:
J. Williams
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