• DocumentCode
    782883
  • Title

    Regularity-constrained pre- and post-filtering for block DCT-based systems

  • Author

    Dai, Wei ; Tran, Trac D.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Johns Hopkins Univ., Baltimore, MD, USA
  • Volume
    51
  • Issue
    10
  • fYear
    2003
  • Firstpage
    2568
  • Lastpage
    2581
  • Abstract
    It is well known that the traditional block transform can only have at most one degree of regularity. In other words, by retaining only one subband, these transforms, including the popular discrete cosine transform (DCT), can only capture the constant signal. The ability to capture polynomials of higher orders is critical in smooth signal approximation, minimizing blocking effects. This paper presents the theory, design, and fast implementation of regularity constrained pre-/post-filters for block-based decomposition systems. We demonstrate that simple pre-/post-filtering modules added to the current block-based infrastructure can help the block transform capture not only the constant signal but the ramp signal as well. Moreover, our proposed framework can be used to generate various fast symmetric M-band wavelets with up to two degrees of regularity.
  • Keywords
    channel bank filters; data compression; digital filters; discrete cosine transforms; filtering theory; image coding; polynomials; transform coding; wavelet transforms; DCT; DCT coding; block DCT-based systems; block-based decomposition systems; block-based infrastructure; block-discrete cosine transform; constant signal; discrete cosine transform; filterbank design; image coding; polynomials; pre-/post-filtering modules; ramp signal; regularity-constrained post-filtering; regularity-constrained pre-filtering; smooth signal approximation; subband; symmetric M-band wavelets; Constraint theory; Decoding; Discrete cosine transforms; Discrete transforms; Helium; Image reconstruction; Polynomials; Quantization; Signal processing; Symmetric matrices;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/TSP.2003.816769
  • Filename
    1232324