Adaptive feature-specific spectral imaging


Conference Paper

We present an architecture for rapid spectral classification in spectral imaging applications. By making use of knowledge gained in prior measurements, our spectral imaging system is able to design adaptive feature-specific measurement kernels that selectively attend to the portions of a spectrum that contain useful classification information. With measurement kernels designed using a probabilistically-weighted version of principal component analysis, simulations predict an orders-of-magnitude reduction in classification error rates. We report on our latest simulation results, as well as an experimental prototype currently under construction. © 2012 SPIE.

Full Text

Duke Authors

Cited Authors

  • Jansen, PA; Dunlop, MJ; Golish, DR; Gehm, ME

Published Date

  • July 23, 2012

Published In

Volume / Issue

  • 8365 /

International Standard Serial Number (ISSN)

  • 0277-786X

International Standard Book Number 13 (ISBN-13)

  • 9780819490438

Digital Object Identifier (DOI)

  • 10.1117/12.918856

Citation Source

  • Scopus