A multi-channel temporally adaptable system for continuous cloud classification from satellite imagery

A multi-channel temporally adaptable system for continuous cloud classification from satellite imagery

A new multi-spectral scheme for cloud classification from satellite imagery is proposed which involves two temporally adaptable probabilistic neural networks, one for the visible and one for the infrared channels. This system offers the ability to perform continuous updating during the whole day. Th...

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Bibliographic Details
Published in:IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222) Vol. 3; pp. 1625 - 1630 vol.3
Main Authors: Azimi-Sadjadi, M.R., Wang, J., Saitwal, K., Reinke, D.
Format: Conference Proceeding
Language:English
Published: IEEE 2001
Subjects:
Atmosphere
Clouds
Electronic mail
Estimation theory
Infrared imaging
Neural networks
Pattern recognition
Probability density function
Satellites
Temperature
Online Access:Get full text
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Summary:A new multi-spectral scheme for cloud classification from satellite imagery is proposed which involves two temporally adaptable probabilistic neural networks, one for the visible and one for the infrared channels. This system offers the ability to perform continuous updating during the whole day. The results using five classes are provided which show the effectiveness of the proposed scheme.
ISBN:0780370449
9780780370449
ISSN:1098-7576
1558-3902
DOI:10.1109/IJCNN.2001.938404