Adaptive feature-specific spectral imaging

P. A. Jansen, M. J. Dunlop, D. R. Golish, M. E. Gehm

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

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.

Original languageEnglish (US)
Title of host publicationCompressive Sensing
DOIs
StatePublished - 2012
EventCompressive Sensing - Baltimore, MD, United States
Duration: Apr 26 2012Apr 27 2012

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume8365
ISSN (Print)0277-786X

Other

OtherCompressive Sensing
CountryUnited States
CityBaltimore, MD
Period4/26/124/27/12

Keywords

  • Adaptive optics
  • Computational sensing
  • Spectral imaging

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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