Home

About

Advanced Search

Browse by Discipline

Scientific Societies

E-print Alerts

Add E-prints

E-print Network
FAQHELPSITE MAPCONTACT US


  Advanced Search  

 
IEEE TRANSACTIONS ON NEURAL NETWORKS, VOL. 15, NO. 1, JANUARY 2004 159 A Temporally Adaptive Classifier for
 

Summary: IEEE TRANSACTIONS ON NEURAL NETWORKS, VOL. 15, NO. 1, JANUARY 2004 159
A Temporally Adaptive Classifier for
Multispectral Imagery
Jianqi Wang, Mahmood R. Azimi-Sadjadi, and Donald Reinke
Abstract--This paper presents a new temporally adaptive classi-
fication system for multispectral images. A spatial­temporal adap-
tation mechanism is devised to account for the changes in the fea-
ture space as a result of environmental variations. Classification
based upon spatial features is performed using Bayesian frame-
work or probabilistic neural networks (PNNs) while the temporal
updating takes place using a spatial­temporal 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 re-
sults on cloud classification from satellite imagery are provided to
show the usefulness of this system.
Index Terms--Bayes classification, cloud classification, multi-
spectral imaging, prediction.
I. INTRODUCTION
MULTISPECTRAL meteorological satellite imaging sys-

  

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

 

Collections: Computer Technologies and Information Sciences