• DocumentCode
    3295250
  • Title

    Detection of ephemeral changes in sequences of images

  • Author

    Theiler, James ; Adler-Golden, Steven M.

  • Author_Institution
    Space & Remote Sensing Sci., Los Alamos Nat. Lab., Los Alamos, NM
  • fYear
    2008
  • fDate
    15-17 Oct. 2008
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    The formalism of anomalous change detection, which was developed for finding unusual changes in pairs of images, is extended to sequences of more than two images. Extended algorithms based on RX, Chronochrome, and Hyper are presented for identifying the most anomalously changing pixels in a sequence of co-registered images. Experimental comparisons are performed both on real data with real anomalies and on real data with simulated anomalies.
  • Keywords
    image sequences; anomalous change detection; ephemeral changes; image sequences; Algorithm design and analysis; Change detection algorithms; Detectors; Gaussian distribution; Laboratories; Lighting; Machine learning; Machine learning algorithms; Pixel; Remote sensing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Applied Imagery Pattern Recognition Workshop, 2008. AIPR '08. 37th IEEE
  • Conference_Location
    Washington DC
  • ISSN
    1550-5219
  • Print_ISBN
    978-1-4244-3125-0
  • Electronic_ISBN
    1550-5219
  • Type

    conf

  • DOI
    10.1109/AIPR.2008.4906469
  • Filename
    4906469