• DocumentCode
    1460288
  • Title

    On Kalman filter solution of space-time interpolation

  • Author

    Chin, Toshio M.

  • Author_Institution
    Jet Propulsion Lab., California Inst. of Technol., Pasadena, CA, USA
  • Volume
    10
  • Issue
    4
  • fYear
    2001
  • fDate
    4/1/2001 12:00:00 AM
  • Firstpage
    663
  • Lastpage
    666
  • Abstract
    The approximate Kalman filtering algorithm presented previously (see ibid., vol.3, p.773-88, Nov. 1994) for image sequence processing can introduce unacceptable negative eigenvalues in the information matrix and can have degraded performance in some applications. The improved algorithm presented in this note guarantees a positive definite information matrix, leading to more stable filter performance
  • Keywords
    Kalman filters; eigenvalues and eigenfunctions; filtering theory; image sequences; interpolation; matrix algebra; Kalman filter solution; approximate Kalman filtering algorithm; image sequence processing; negative eigenvalues; positive definite information matrix; space-time interpolation; stable filter performance; Covariance matrix; Eigenvalues and eigenfunctions; Geophysics computing; Image reconstruction; Image sequences; Interpolation; Kalman filters; Markov random fields; Satellites; Sparse matrices;
  • fLanguage
    English
  • Journal_Title
    Image Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1057-7149
  • Type

    jour

  • DOI
    10.1109/83.913601
  • Filename
    913601