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1098 IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 41, NO. 5, MAY 2003 A Multichannel Temporally Adaptive System
 

Summary: 1098 IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 41, NO. 5, MAY 2003
A Multichannel Temporally Adaptive System
for Continuous Cloud Classification
From Satellite Imagery
Kishor Saitwal, Student Member, IEEE, Mahmood R. Azimi-Sadjadi, and Donald Reinke
Abstract--A two-channel temporal updating system is pre-
sented, which accounts for feature changes in the visible and
infrared satellite images. The system uses two probabilistic neural
network classifiers and a context-based predictor to perform con-
tinuous cloud classification during the day and night. Test results
for 27 h of continuous classification and updating are presented on
a sequence of Geostationary Operational Environmental Satellite
8 images. Further test results of the system on two new sets of
data with 12 weeks time difference are also presented that show
the potential of this system as an operational continuous cloud
classification system.
Index Terms--Cloud classification, multispectral satellite
imaging, probabilistic neural networks.
I. INTRODUCTION
THE GEOSTATIONARY Operational Environmental

  

Source: Azimi-Sadjadi, Mahmood R. - Department of Electrical and Computer Engineering, Colorado State University

 

Collections: Computer Technologies and Information Sciences