DocumentCode :
508408
Title :
Registration of Remote Sensing Images Based on the Relevance Vector Machine
Author :
Wang, Xiaofei ; Zhang, Junping ; Zhang, Ye
Author_Institution :
Dept. of Inf. Eng., Harbin Inst. of Technol., Harbin, China
Volume :
1
fYear :
2009
fDate :
14-16 Aug. 2009
Firstpage :
547
Lastpage :
551
Abstract :
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.
Keywords :
computational geometry; image registration; learning (artificial intelligence); remote sensing; geometric transformation model; image registration; nonlinear geometric distortion; relevance vector machine; remote sensing; Distortion measurement; Educational institutions; Geometry; Image registration; Image resolution; Nonlinear distortion; Pixel; Polynomials; Remote sensing; Solid modeling; Registration; Remote Sensing Image; relevance vector machine (RVM);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3736-8
Type :
conf
DOI :
10.1109/ICNC.2009.583
Filename :
5367192
Link To Document :
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