• DocumentCode
    1253487
  • Title

    Lifting scheme for biorthogonal multiwavelets originated from Hermite splines

  • Author

    Averbuch, Amir Z. ; Zheludev, Valery A.

  • Author_Institution
    Sch. of Comput. Sci., Tel Aviv Univ., Israel
  • Volume
    50
  • Issue
    3
  • fYear
    2002
  • fDate
    3/1/2002 12:00:00 AM
  • Firstpage
    487
  • Lastpage
    500
  • Abstract
    We present new multiwavelet transforms of multiplicity 2 for manipulation of discrete-time signals. The transforms are implemented in two phases: (1) pre(post)-processing, which transforms the scalar signal into a vector signal (and back) and (2) wavelet transforms of the vector signal. Both phases are performed in a lifting manner. We use the cubic interpolatory Hermite splines as a predicting aggregate in the vector wavelet transform. We present new pre(post)-processing algorithms that do not degrade the approximation accuracy of the vector wavelet transforms. We describe two types of vector wavelet transforms that are dual to each other but have similar properties and three pre(post)processing algorithms. As a result, we get fast biorthogonal algorithms to transform discrete-time signals that are exact on sampled cubic polynomials. The bases for the transform are symmetric and have short support
  • Keywords
    channel bank filters; data compression; filtering theory; image coding; interpolation; signal processing; splines (mathematics); transform coding; wavelet transforms; analysis wavelets; approximation accuracy; biorthogonal multiwavelets; cubic interpolatory Hermite splines; discrete-time signals; fast biorthogonal algorithms; image compression; lifting scheme; multifilter banks; multiwavelet transforms; post-processing algorithms; pre-processing algorithms; sampled cubic polynomials; scalar signal; short support transform; symmetric transform; synthesis wavelets; vector signal; vector wavelet transforms; Aggregates; Approximation algorithms; Degradation; Discrete transforms; Discrete wavelet transforms; Multiresolution analysis; Polynomials; Signal processing algorithms; Wavelet analysis; Wavelet transforms;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/78.984720
  • Filename
    984720