• DocumentCode
    7181
  • Title

    Endmember Variability in Hyperspectral Analysis: Addressing Spectral Variability During Spectral Unmixing

  • Author

    Zare, Alina ; Ho, K.C.

  • Author_Institution
    Electr. & Comput. Eng., Univ. of Missouri, Columbia, MO, USA
  • Volume
    31
  • Issue
    1
  • fYear
    2014
  • fDate
    Jan. 2014
  • Firstpage
    95
  • Lastpage
    104
  • Abstract
    Variable illumination and environmental, atmospheric, and temporal conditions cause the measured spectral signature for a material to vary within hyperspectral imagery. By ignoring these variations, errors are introduced and propagated throughout hyperspectral image analysis. To develop accurate spectral unmixing and endmember estimation methods, a number of approaches that account for spectral variability have been developed. This article motivates and provides a review for methods that account for spectral variability during hyperspectral unmixing and endmember estimation and a discussion on topics for future work in this area.
  • Keywords
    geophysical image processing; support vector machines; endmember estimation methods; endmember variability; hyperspectral image analysis; hyperspectral unmixing; spectral variability; support vector machines; Atmospheric measurements; Estimation; Hyperspectral imaging; Lighting; Materials; Support vector machines;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Magazine, IEEE
  • Publisher
    ieee
  • ISSN
    1053-5888
  • Type

    jour

  • DOI
    10.1109/MSP.2013.2279177
  • Filename
    6678271