Extraction of information from hyperspectral imagery using wavelets

C. O. L. Stietzel; Joel A. Rosiene

doi:10.1117/12.170092

15 March 1994 Extraction of information from hyperspectral imagery using wavelets

C. O. L. Stietzel, Joel A. Rosiene

Proceedings Volume 2242, Wavelet Applications; (1994) https://doi.org/10.1117/12.170092
Event: SPIE's International Symposium on Optical Engineering and Photonics in Aerospace Sensing, 1994, Orlando, FL, United States

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.

Citation Download Citation

C. O. L. Stietzel and Joel A. Rosiene "Extraction of information from hyperspectral imagery using wavelets", Proc. SPIE 2242, Wavelet Applications, (15 March 1994); https://doi.org/10.1117/12.170092

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