• DocumentCode
    2355642
  • Title

    A multiresolution approach for video texture registration

  • Author

    Bonneau, Robert J. ; Novak, Mark E. ; Perretta, James S. ; Ertan, Sevgi

  • Author_Institution
    AFRL/SNRT, Rome, NY, USA
  • fYear
    2001
  • fDate
    1-12 Oct 2001
  • Firstpage
    126
  • Lastpage
    128
  • Abstract
    Electro-optical imagery can have uniform characteristics that prevent it from being registered by conventional edge-based methods. Such uniform characteristics, if they have periodicity, can be exploited using multi-resolution texture extraction techniques. We first use a multi-resolution Markov model to represent electro-optical textures and apply an autoregressive statistical approach to find correspondence between two images. We then demonstrate how this approach reduces the computational complexity of registering of two successive frames of video
  • Keywords
    Markov processes; autoregressive processes; computational complexity; feature extraction; image registration; autoregressive statistical approach; computational complexity; edge-based methods; electro-optical imagery; multiresolution Markov model; multiresolution approach; multiresolution texture extraction; video texture registration; Computational complexity; Data structures; Equations; Filter bank; Image resolution; Markov random fields; Multiresolution analysis; Signal resolution; Video compression; Wavelet transforms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Applied Imagery Pattern Recognition Workshop, AIPR 2001 30th
  • Conference_Location
    Washington, DC
  • Print_ISBN
    0-7695-1245-3
  • Type

    conf

  • DOI
    10.1109/AIPR.2001.991214
  • Filename
    991214