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Proceedings Paper

Extraction of information from hyperspectral imagery using wavelets
Author(s): C. O. L. Stietzel; Joel A. Rosiene
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Paper Abstract

An airborne test platform known as the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) has been in operation since 1989. The data gathered form AVIRIS comes in 224 bands covering the 0.4 - 2.4micrometers range of the electromagnetic spectrum. The bands are spaced approximately 10nm apart with a bandwidth of just 10nm. Thus AVIRIS provides a nearly continuous spectral signature for a ground area 20m square. Because of the high dimensionality of such data, previous techniques for extracting information from multispectral imagery become computationally prohibitive. In the technique presented the wavelet transform is used to select features in the spectral signature on which the classification of the AVIRIS data set is carried out. The ability of the wavelet transform to localize both in time and frequency may make the technique able to characterize absorption bands better than many other transform techniques. The results of the technique will be compared against a classification using coefficients of the discrete cosine transform as features and a classification of the original data set.

Paper Details

Date Published: 15 March 1994
PDF: 10 pages
Proc. SPIE 2242, Wavelet Applications, (15 March 1994); doi: 10.1117/12.170092
Show Author Affiliations
C. O. L. Stietzel, Univ. of Connecticut (United States)
Joel A. Rosiene, Univ. of Connecticut (United States)

Published in SPIE Proceedings Vol. 2242:
Wavelet Applications
Harold H. Szu, Editor(s)

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