• DocumentCode
    1013874
  • Title

    Self-lifting scheme: new approach for generating and factoring wavelet filter bank

  • Author

    Chen, X.X. ; Chen, Y.Y.

  • Author_Institution
    Nat. Eng. Res. Center for T & D, China Electr. Power Res. Inst., Beijing
  • Volume
    2
  • Issue
    4
  • fYear
    2008
  • fDate
    12/1/2008 12:00:00 AM
  • Firstpage
    405
  • Lastpage
    414
  • Abstract
    The authors presents a new lifting scheme, the self-lifting scheme, and prove that self-lifted wavelets based on orthogonal or biorthogonal wavelets remain biorthogonal. In contrast to self-lifting, the existing lifting scheme can be called cross-lifting. Compared with cross-lifting, the self-lifting scheme provides new approaches for constructing biorthogonal wavelets, as well as factorising wavelet filter bank (WFB). For constructing wavelets, the self-lifting-based method updates one part of a wavelet filter by the other part of the same filter and obtains two updated filters in one pass, whereas the cross-lifting based method updates one filter by another filter and obtains one updated filter in one pass. To factorise WFB, self-lifting takes one part of a filter as the factor to decompose the other part of the same filter and obtains two factorised filters in one pass, whereas cross-lifting based one takes one part of a filter as the factor to decompose the corresponding part of the other filter and obtains one factorised filter in one pass. Several examples show how to use self-lifting scheme to produce new wavelets with desirable properties, how to factorise complex WFBs into simple lifting filter banks, how to implement self-lifting-based discrete wavelet transform (WT) in z-domain and in time domain and why lifting-based WT is superior to convolution-based one.
  • Keywords
    channel bank filters; discrete wavelet transforms; biorthogonal wavelets; cross-lifting based method; discrete wavelet transform; orthogonal wavelets; self-lifting wavelets; wavelet filter bank;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IET
  • Publisher
    iet
  • ISSN
    1751-9675
  • Type

    jour

  • DOI
    10.1049/iet-spr:20070166
  • Filename
    4693976