Canonical correlation analysis for assessing the performance of adaptive spectral imagers

Zhipeng Wang, Biliana Paskalova, J. Scott Tyo, M. M. Hayat

Research output: Contribution to journalConference article

9 Scopus citations

Abstract

A new class of spectrally adaptive infrared detectors has been reported recently that has a pectral response function that can be altered electronically by controlling the bias voltage of the photodetector. Unlike conventional sensors, these new sensors have "bands" that have highly correlated spectral responses. The potential benefit of these sensors is that the number of bands (and their spectral features) used can be adapted to a specific task. The drawback is that there might not be enough spectral diversity to perform detection and classification operations. In this paper we present a new theory that describes the suitability of an arbitrary spectral sensor to perform a specific spectral detection/classification task. This theory is based on the geometric relationships between the sensor space that describes the spectral characteristics of the detector and a scene space that contains the spectra to be observed. We adapt the theory of canonical correlation analysis to provide a rigorous framework for assessing the utility of spectral detectors. We also show that this general theory encompasses traditional band selection methods, but provides much greater flexibility and a more transparent and intuitive explanation of the phenomenology.

Original languageEnglish (US)
Article number95
Pages (from-to)23-34
Number of pages12
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume5806
Issue numberPART I
DOIs
StatePublished - Nov 10 2005
EventAlgorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XI - Orlando, FL, United States
Duration: Mar 28 2005Apr 1 2005

Keywords

  • Adaptive spectral imaging
  • Band selection
  • Feature extraction
  • Feature space
  • Pattern space
  • Scene space
  • Sensor space
  • Spectral imaging system modeling

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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