A temporally adaptive classifier for multispectral imagery

IEEE Transactions on Neural Networks
Jianqi WangD L Reinke

Abstract

This paper presents a new temporally adaptive classification system for multispectral images. A spatial-temporal adaptation mechanism is devised to account for the changes in the feature space as a result of environmental variations. Classification based upon spatial features is performed using Bayesian framework or probabilistic neural networks (PNNs) while the temporal updating takes place using a spatial-temporal predictor. A simple iterative updating mechanism is also introduced for adjusting the parameters of these systems. The proposed methodology is used to develop a pixel-based cloud classification system. Experimental results on cloud classification from satellite imagery are provided to show the usefulness of this system.

References

Feb 7, 2008·IEEE Transactions on Neural Networks·B TianD L Reinke

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Citations

Jul 22, 2006·IEEE Transactions on Neural Networks·Youshen Xia, Henry Leung
Dec 5, 2008·IEEE Transactions on Neural Networks·Cesare Alippi, Manuel Roveri
May 29, 2007·IEEE Transactions on Neural Networks·Aristeidis DiplarosTheo Gevers
Jul 21, 2010·IEEE Transactions on Neural Networks·Thanh Minh NguyenSiddhant Ahuja

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