Knowledge based weather image processing and classification

Author

Siddiqui, Khalid J.

Author_Institution

Dept. of Comput. Sci., State Univ. of New York, Fredonia, NY, USA

Volume

4

fYear

1997

fDate

3-8 Aug 1997

Firstpage

1944

Abstract

Satellite imagery of weather patterns and meteorological information are used to develop a knowledge based weather image processing and classification system (KB/WIS). Wavelet and fractal methods are used to extract features from weather images. The features extracted are used to represent various weather patterns. The system is statistically trained to characterize and interpret weather patterns. The system is a composite of four components: image acquisition, image preprocessing and enhancement, feature extraction and selection, and weather inference engine. Complete architecture of the KB/WIS system including its applications is described

Keywords

atmospheric techniques; feature extraction; fractals; geophysical signal processing; geophysics computing; image classification; image enhancement; image processing; inference mechanisms; knowledge based systems; meteorology; remote sensing; wavelet transforms; KB WIS; KB/WIS; atmosphere; feature extraction; fractal method; image acquisition; image classification; image enhancement; inference engine; knowledge based weather image processing; measurement technique; meteorology; optical imaging; preprocessing; remote sensing; satellite imagery; statistical training; wavelet transform; weather pattern; Atmosphere; Atmospheric modeling; Earth; Feature extraction; Humans; Image processing; Load forecasting; Mathematical model; Predictive models; Weather forecasting;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing, 1997. IGARSS '97. Remote Sensing - A Scientific Vision for Sustainable Development., 1997 IEEE International

Print_ISBN

0-7803-3836-7

Type

conf

DOI

10.1109/IGARSS.1997.609156

Filename

609156