Super-resolution mapping of the shoreline through soft classification analogues
Super-resolution mapping of the shoreline through soft classification analogues
Methods for mapping the shoreline at a sub-pixel level are evaluated. The most accurate predictions of shoreline location were made from an approach based on simulated annealing applied to the output of a soft classification (RMSE=2.25 m).
Foody, G.M.
06e50027-603d-4a5b-88f5-af2bb6235a37
Muslim, A.M.
628ed733-f4bc-4afc-a83f-053249b5bf52
Atkinson, P.M.
aaaa51e4-a713-424f-92b0-0568b198f425
2003
Foody, G.M.
06e50027-603d-4a5b-88f5-af2bb6235a37
Muslim, A.M.
628ed733-f4bc-4afc-a83f-053249b5bf52
Atkinson, P.M.
aaaa51e4-a713-424f-92b0-0568b198f425
Foody, G.M., Muslim, A.M. and Atkinson, P.M.
(2003)
Super-resolution mapping of the shoreline through soft classification analogues.
In Proceedings of IGARSS 2003.
IEEE.
3 pp
.
Record type:
Conference or Workshop Item
(Paper)
Abstract
Methods for mapping the shoreline at a sub-pixel level are evaluated. The most accurate predictions of shoreline location were made from an approach based on simulated annealing applied to the output of a soft classification (RMSE=2.25 m).
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Published date: 2003
Additional Information:
also on CD-ROM
Venue - Dates:
IGARSS 2003 Conference, Toulouse, France, 2003-07-20 - 2003-07-24
Identifiers
Local EPrints ID: 14547
URI: http://eprints.soton.ac.uk/id/eprint/14547
PURE UUID: 8245b4f0-ce1b-4b5e-a597-f08a8a198f2d
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Date deposited: 16 Feb 2005
Last modified: 11 Dec 2021 13:52
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Contributors
Author:
G.M. Foody
Author:
A.M. Muslim
Author:
P.M. Atkinson
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