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Stochastic spectral unmixing with enhanced endmember class separation

Michael T Eismann1, Russell C Hardie

  • 1Air Force Research Laboratory, AFRL/SNJT, Wright Patterson Air Force Base, Ohio 45433-7700, USA. michael.eismann@wpafb.af.mil

Applied Optics
|January 14, 2005
PubMed
Summary

This study enhances the stochastic mixing model (SMM) algorithm for hyperspectral imagery spectral unmixing. The improved SMM offers better statistical representation and endmember class separation for analyzing complex spectral data.

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