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A search algorithm to meta-optimize the parameters for an extended Kalman filter to improve classification on hyper-temporal images
Citation
Salmon, BP and Kleynhans, W and van den Bergh, F and Olivier, JC and Marais, WJ and Grobler, TL and Wessels, KJ, A search algorithm to meta-optimize the parameters for an extended Kalman filter to improve classification on hyper-temporal images, Proceedings of the IEEE International Geoscience and Remote Sensing Symposium 2012, 22-27 July, Munich, pp. 4974-4977. ISBN 978-1-4673-1159-5 (2012) [Refereed Conference Paper]
Copyright Statement
Copyright 2012 IEEE
DOI: doi:10.1109/IGARSS.2012.6352495
Abstract
In this paper the Bias Variance Search Algorithm is proposed
as an algorithm to optimize a candidate set of initial parameters
for an Extended Kalman filter (EKF). The search algorithm
operates on a Bias Variance Equilibrium Point criterion
to determine how to set the initial parameters. The candidate
set is then used by the EKF to estimate state parameters
to fit a triply modulated cosine function to time series of the
first two spectral bands of the MODerate-resolution Imaging
Spectroradiometer (MODIS) land product. The state parameters
are then used for land cover classification. The results
of the search algorithm was tested on classifying land cover
in the Limpopo province, South Africa. An improvement in
land cover classification was observed when the method was
compared to a robust regression method.
Item Details
| Item Type: | Refereed Conference Paper |
|---|---|
| Keywords: | Hellinger distance, Kalman filter, time series analysis, spatial information |
| Research Division: | Engineering |
| Research Group: | Communications engineering |
| Research Field: | Signal processing |
| Objective Division: | Environmental Management |
| Objective Group: | Other environmental management |
| Objective Field: | Other environmental management not elsewhere classified |
| UTAS Author: | Salmon, BP (Dr Brian Salmon) |
| UTAS Author: | Olivier, JC (Professor JC Olivier) |
| ID Code: | 82340 |
| Year Published: | 2012 |
| Deposited By: | Engineering |
| Deposited On: | 2013-01-25 |
| Last Modified: | 2017-11-06 |
| Downloads: | 1 View Download Statistics |
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