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2009 Fifth International Conference on Natural Computation
Registration of Remote Sensing Images Based on the Relevance Vector Machine
Tianjian, China
August 14-August 16
ISBN: 978-0-7695-3736-8
ASCII Text
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Xiaofei Wang, Junping Zhang, Ye Zhang, "Registration of Remote Sensing Images Based on the Relevance Vector Machine," 2013 International Conference on Computing, Networking and Communications (ICNC), vol. 1, pp. 547-551, 2009 Fifth International Conference on Natural Computation, 2009.
 
 
BibTex
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@article{ 10.1109/ICNC.2009.583,
author = {Xiaofei Wang and Junping Zhang and Ye Zhang},
title = {Registration of Remote Sensing Images Based on the Relevance Vector Machine},
journal ={2013 International Conference on Computing, Networking and Communications (ICNC)},
volume = {1},
year = {2009},
isbn = {978-0-7695-3736-8},
pages = {547-551},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICNC.2009.583},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - 2013 International Conference on Computing, Networking and Communications (ICNC)
TI - Registration of Remote Sensing Images Based on the Relevance Vector Machine
SN - 978-0-7695-3736-8
SP547
EP551
A1 - Xiaofei Wang,
A1 - Junping Zhang,
A1 - Ye Zhang,
PY - 2009
KW - Remote Sensing Image
KW - Registration
KW - relevance vector machine (RVM)
VL - 1
JA - 2013 International Conference on Computing, Networking and Communications (ICNC)
ER -
 
Remote sensing has become a technique of indispensable importance for us to acquire the information on the ground. In the process of imaging, geometric distortion occurs due to several factors, which causes many difficulties when using those remote images for change detection, information fusion, resolution enhancement and so on. So the image registration is necessary. Aiming at the distortion type for the selection of geometric transformation model in the registration process, a relevance vector machine (RVM) based geometric transformation model is given, which will solve the problem of nonlinear geometric distortion efficiently as well as avoiding the shortcomings in the traditional model. Experiments have been realized this method.
Index Terms:
Remote Sensing Image, Registration, relevance vector machine (RVM)
Citation:
Xiaofei Wang, Junping Zhang, Ye Zhang, "Registration of Remote Sensing Images Based on the Relevance Vector Machine," icnc, vol. 1, pp.547-551, 2009 Fifth International Conference on Natural Computation, 2009
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