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Please use this identifier to cite or link to this item: http://hdl.handle.net/10204/5839

Title: Meta-optimization of the extended kalman filter's parameters for improved feature extraction on hyper-temporal images
Authors: Salmon, BP
Kleynhans, W
Van den Bergh, F
Olivier, JC
Marais, WJ
Wessels, KJ
Keywords: Hellinger distance
Kalman filter
Time series analysis
Unsupervised learning
Spatial information
Issue Date: Jul-2011
Publisher: IEEE
Citation: Salmon, BP, Kleynhans, W, Van den Bergh, F, Olivier, JC, Marais, WJ and Wessels, KJ. 2011. Meta-optimization of the extended kalman filter's parameters for improved feature extraction on hyper-temporal images. 2011 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Vancouver, Canada, 24-29 July 2011
Series/Report no.: Workflow;8092
Abstract: Time series derived from the first two spectral bands of the MODerate-resolution Imaging Spectroradiometer (MODIS) land surface reflectance product can be modelled as a pair of triply (mean, phase and amplitude) modulated cosine functions. This paper proposes a meta-optimization approach for setting the parameters of the non-linear Extended Kalman Filter to rapidly and efficiently estimate the features for the pair of triply modulated cosine functions. The approach is based on a unsupervised search algorithm over an appropriately defined manifold using spatial and temporal information. Performance of the new method is compared to other applicable methods and is tested on the Gauteng province which is South Africa’s province with the fastest growing economy.
Description: 2011 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Vancouver, Canada, 24-29 July 2011
URI: http://ieeexplore.ieee.org/application/enterprise/entconfirmation.jsp?arnumber=6049730
http://hdl.handle.net/10204/5839
ISBN: 978-1-4577-1003-2
Appears in Collections:Earth observation
General science, engineering & technology
Earth observation technologies

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