Skip to main content

Adaptive feature-specific spectral imaging classifier (AFSSI-C)

Publication ,  Journal Article
Dunlop, M; Poon, P; Gehm, M; Golish, D; Vera, E
Published in: Proceedings of the International Telemetering Conference
December 1, 2013

The AFSSI-C is a spectral imager that generates spectral classification directly, in fewer measurements than are required by traditional systems that measure the spectral datacube (which is later interpreted to make material classification). By utilizing adaptive features to constantly update conditional probabilities for the different hypotheses, the AFSSI-C avoids the overhead of directly measuring every element in the spectral datacube. The system architecture, feature design methodology, simulation results, and preliminary experimental results are given.

Duke Scholars

Published In

Proceedings of the International Telemetering Conference

ISSN

0884-5123

Publication Date

December 1, 2013

Volume

49
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Dunlop, M., Poon, P., Gehm, M., Golish, D., & Vera, E. (2013). Adaptive feature-specific spectral imaging classifier (AFSSI-C). Proceedings of the International Telemetering Conference, 49.
Dunlop, M., P. Poon, M. Gehm, D. Golish, and E. Vera. “Adaptive feature-specific spectral imaging classifier (AFSSI-C).” Proceedings of the International Telemetering Conference 49 (December 1, 2013).
Dunlop M, Poon P, Gehm M, Golish D, Vera E. Adaptive feature-specific spectral imaging classifier (AFSSI-C). Proceedings of the International Telemetering Conference. 2013 Dec 1;49.
Dunlop, M., et al. “Adaptive feature-specific spectral imaging classifier (AFSSI-C).” Proceedings of the International Telemetering Conference, vol. 49, Dec. 2013.
Dunlop M, Poon P, Gehm M, Golish D, Vera E. Adaptive feature-specific spectral imaging classifier (AFSSI-C). Proceedings of the International Telemetering Conference. 2013 Dec 1;49.

Published In

Proceedings of the International Telemetering Conference

ISSN

0884-5123

Publication Date

December 1, 2013

Volume

49