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Proceedings Paper

Autonomous determination of endmembers in high spatial and spectral resolution data
Author(s): Edwin M. Winter; Christopher G. Simi; Anthony B. Hill; Christopher LaSota; Michael E. Winter
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Paper Abstract

Recently, new hyperspectral sensors have become available that provide both high spatial resolution and high spectral resolution. These characteristics combined with high signal to noise ratio allow the differentiation of vegetation or mineral types based upon the spectra of small patches of the surface. In this paper, automated endmember determination methods are applied to high spatial and spectral resolution data from two new sensors, TRWIS III and NVIS. Both of these sensors are high quality low noise pushbroom imaging spectrometers that acquire data at 5 to 6 nm resolution from 400 to 2450 nm. The data sets collected will be used for two different applications of the automated determination of endmembers: scene material classification and the detection of spectral anomalies. The NVIS hyperspectral data was collected from approximately 6000 ft above ground level over Cuprite, Nevada, resulting in a footprint of approximately two meters. The TRWIS III data was collected from 1500 meters altitude over mixed agriculture backgrounds in Ventura County, California, a largely agricultural area about 100 km from Los Angeles. After calibration and other preprocessing steps, the data in each case was processed using the N-FINDR algorithm, which extracts endmembers based upon the geometry of convex sets. Once these endmember spectra are found, the image cube can be "unmixed" into fractional abundances of each material in each pixel. The results of processing this high spatial and spectral resolution data for these two different applications will be presented.

Paper Details

Date Published: 23 August 2000
PDF: 7 pages
Proc. SPIE 4049, Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI, (23 August 2000); doi: 10.1117/12.410374
Show Author Affiliations
Edwin M. Winter, Technical Research Associates, Inc. (United States)
Christopher G. Simi, U.S. Army Night Vision & Electronic Sensors Directorate (United States)
Anthony B. Hill, U.S. Army Night Vision & Electronic Sensors Directorate (United States)
Christopher LaSota, E-OIR Measurements, Inc. (United States)
Michael E. Winter, Univ. of Hawaii (Australia)


Published in SPIE Proceedings Vol. 4049:
Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI
Sylvia S. Shen; Michael R. Descour, Editor(s)

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