• DocumentCode
    745167
  • Title

    On constrained energy minimization and the partial unmixing of multispectral images

  • Author

    Settle, Jeff

  • Author_Institution
    Environ. Syst. Sci. Centre, Reading Univ., UK
  • Volume
    40
  • Issue
    3
  • fYear
    2002
  • fDate
    3/1/2002 12:00:00 AM
  • Firstpage
    718
  • Lastpage
    721
  • Abstract
    Constrained energy minimization, a target detection algorithm, sometimes appears to correlate well with fractional abundance. This letter shows that exact correlation with true relative abundance arises when the following conditions hold: underlying mixing is linear, end-members are well separated with respect to random noise, and global abundances are constrained in a particular way
  • Keywords
    feature extraction; geophysical signal processing; image recognition; minimisation; remote sensing; constrained energy minimization; end-members; fractional abundance; global abundances; hyperspectral data; minimization; multispectral images; partial demixing; random noise; target detection algorithm; underlying mixing; 1f noise; Availability; Hyperspectral imaging; Hyperspectral sensors; Image sensors; Matched filters; Minimization methods; Multispectral imaging; Object detection; Pixel;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/TGRS.2002.1000332
  • Filename
    1000332