Material taxonomy for object identification in HYDICE imagery

Edward M. Bassett; Linda S. Kalman

doi:10.1117/12.257175

6 November 1996 Material taxonomy for object identification in HYDICE imagery

Edward M. Bassett, Linda S. Kalman

Proceedings Volume 2821, Hyperspectral Remote Sensing and Applications; (1996) https://doi.org/10.1117/12.257175
Event: SPIE's 1996 International Symposium on Optical Science, Engineering, and Instrumentation, 1996, Denver, CO, United States

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.

Citation Download Citation

Edward M. Bassett and Linda S. Kalman "Material taxonomy for object identification in HYDICE imagery", Proc. SPIE 2821, Hyperspectral Remote Sensing and Applications, (6 November 1996); https://doi.org/10.1117/12.257175

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