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

Matthew Dunlop, Phillip Poon, Michael Gehm, Dathon Golish, Esteban Vera

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations


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.

Original languageEnglish
JournalProceedings of the International Telemetering Conference
StatePublished - 2013
Externally publishedYes
EventITC/USA 2013: 49th Annual International Telemetering Conference and Technical Exhibition - Meeting all the Challenges of Telemetry, 2013 - Las Vegas,NV, United States
Duration: 21 Oct 201324 Oct 2013


  • Compressive sensing
  • Hyperspectral imaging
  • Spectral imager


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