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Meta-optimization of the extended kalman filter's parameters for improved feature extraction on hyper-temporal images

Citation

Salmon, BP and Kleynhans, W and van den Bergh, F and Olivier, JC and Marais, WJ and Wessels, KJ, Meta-optimization of the extended kalman filter's parameters for improved feature extraction on hyper-temporal images, Proceedings of the IEEE Geoscience and Remote Sensing Symposium (IGARSS) 2011, 24-29 July 2011, Vancouver, Canada, pp. 2543-2546. ISBN 978-1-4577-1003-2 (2011) [Refereed Conference Paper]

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.

Item Details

Item Type:Refereed Conference Paper
Keywords:Hellinger distance, Kalman filter, time series analysis, unsupervised learning, spatial information
Research Division:Engineering
Research Group:Electrical and Electronic Engineering
Research Field:Electrical and Electronic Engineering not elsewhere classified
Objective Division:Expanding Knowledge
Objective Group:Expanding Knowledge
Objective Field:Expanding Knowledge in Engineering
Author:Salmon, BP (Dr Brian Salmon)
Author:Olivier, JC (Professor JC Olivier)
ID Code:78839
Year Published:2011
Deposited By:Engineering
Deposited On:2012-07-30
Last Modified:2017-11-06
Downloads:0

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