Geometrical interpretation of the adaptive coherence estimator for hyperspectral target detection

Shahar Bar, Ori Bass, Alon Volfman, Tomer Dallal, Stanley R. Rotman

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

A hyperspectral cube consists of a set of images taken at numerous wavelengths. Hyperspectral image data analysis uses each material's distinctive patterns of reflection, absorption and emission of electromagnetic energy at specific wavelengths for classification or detection tasks. Because of the size of the hyperspectral cube, data reduction is definitely advantageous; when doing this, one wishes to maintain high performances with the least number of bands. Obviously in such a case, the choice of the bands will be critical. In this paper, we will consider one particular algorithm, the adaptive coherence estimator (ACE) for the detection of point targets. We give a quantitative interpretation of the dependence of the algorithm on the number and identity of the bands that have been chosen. Results on simulated data will be presented.

Original languageEnglish
Title of host publicationAlgorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIX
DOIs
StatePublished - 12 Aug 2013
EventAlgorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIX - Baltimore, MD, United States
Duration: 29 Apr 20132 May 2013

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume8743
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceAlgorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIX
Country/TerritoryUnited States
CityBaltimore, MD
Period29/04/132/05/13

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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