• DocumentCode
    284936
  • Title

    Optimal linear filters for pyramidal decomposition

  • Author

    Gurski, Gregory C. ; Orchard, Michael T. ; Hull, Andrew W.

  • Author_Institution
    Coordinated Sci. Lab., Illinois Univ., Urbana, IL, USA
  • Volume
    4
  • fYear
    1992
  • fDate
    23-26 Mar 1992
  • Firstpage
    633
  • Abstract
    A method for determining the optimal linear filters for use in pyramidal decompositions under the minimum mean square error criterion is presented. The pyramidal structure has analysis and interpolation filters. The equations describing the optimal filters are nonlinear in the filter coefficients, making direct solution intractable. However, the optimal filters can be determined by iteratively solving for the optimal analysis and interpolation filters. This leads to a linear system of equations that can be solved using least squares or QR factorization. The optimization is valid in a data dependent or stochastic setting. Convergence and computational complexity of the algorithm are discussed. Some results of optimal linear filters applied to images are presented
  • Keywords
    computational complexity; convergence of numerical methods; filtering and prediction theory; image processing; interpolation; signal processing; QR factorization; algorithm; analysis filter; computational complexity; convergence; data dependent setting; images; interpolation filters; iterative solution; least squares; linear system of equations; minimum mean square error criterion; nonlinear equations; optimal linear filters; pyramidal decomposition; stochastic setting; Finite impulse response filter; Image reconstruction; Interpolation; Linear systems; Low pass filters; Mean square error methods; Nonlinear equations; Nonlinear filters; Signal analysis; Signal processing algorithms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech, and Signal Processing, 1992. ICASSP-92., 1992 IEEE International Conference on
  • Conference_Location
    San Francisco, CA
  • ISSN
    1520-6149
  • Print_ISBN
    0-7803-0532-9
  • Type

    conf

  • DOI
    10.1109/ICASSP.1992.226318
  • Filename
    226318