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

Domaine:

geospatial

Type de record:

paper
Créateur:
BriKlevanJan
Hôte:avatar
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.

Visit

figshare.com

Tasks

computer vision

Tags

Electrical engineering not elsewhere classifiedHellinger distanceKalman filtertime series analysisunsupervised learningspatial information

Licenses

In CopyrightEmbargoed

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