• DocumentCode
    815987
  • Title

    Separability of spatiotemporal spectra of image sequences

  • Author

    Eckert, Michael P. ; Buchsbaum, Gershon ; Watson, Andrew B.

  • Author_Institution
    Dept. of Bioeng., Pennsylvania Univ., Philadelphia, PA, USA
  • Volume
    14
  • Issue
    12
  • fYear
    1992
  • fDate
    12/1/1992 12:00:00 AM
  • Firstpage
    1210
  • Lastpage
    1213
  • Abstract
    The authors calculate the spatiotemporal power spectrum of 14 image sequences in order to determine the degree to which the spectra are separable in space and time and to assess the validity of the commonly used exponential correlation model. They expand the spectrum by a singular value decomposition into a sum of separable terms and define an index of spatiotemporal separability. as the fraction of the signal energy that can be represented by the first (largest) separable term. All spectra were found to be highly separable with an index of separability above 0.98. The power spectra of the sequences were well fit by a separable model, which corresponds to a product of exponential autocorrelation functions separable in space and time
  • Keywords
    image sequences; spectral analysis; exponential correlation model; image sequences; singular value decomposition; spatiotemporal power spectrum; spatiotemporal separability; Autocorrelation; Biological system modeling; Cameras; Frequency conversion; Image coding; Image sequences; Layout; Pixel; Spatiotemporal phenomena; Statistics;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/34.177387
  • Filename
    177387