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Proceedings Paper

Material taxonomy for object identification in HYDICE imagery
Author(s): Edward M. Bassett; Linda S. Kalman
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Paper Abstract

This paper summarizes investigations made at The Aerospace Corporation, during the past year, in the field of hyperspectral material identification. A spectral feature metric which makes use of visible features in the `graph' of a reference spectrum or acquired hyperspectral sample was developed and refined. Using this, and other well-known spectral similarity metrics, a mechanism for creating material taxonomies using clustering techniques was developed. The taxonomies and metrics were combined to create an innovative means for identifying materials and objects in hyperspectral scenes from the HYDICE sensor.

Paper Details

Date Published: 6 November 1996
PDF: 12 pages
Proc. SPIE 2821, Hyperspectral Remote Sensing and Applications, (6 November 1996); doi: 10.1117/12.257175
Show Author Affiliations
Edward M. Bassett, The Aerospace Corp. (United States)
Linda S. Kalman, The Aerospace Corp. (United States)

Published in SPIE Proceedings Vol. 2821:
Hyperspectral Remote Sensing and Applications
Sylvia S. Shen, Editor(s)

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