• DocumentCode
    1383666
  • Title

    Adaptive polyphase subband decomposition structures for image compression

  • Author

    Gerek, Ömer Nezih ; Çetin, A. Enis

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Anadola Univ., Eskisehir, Turkey
  • Volume
    9
  • Issue
    10
  • fYear
    2000
  • fDate
    10/1/2000 12:00:00 AM
  • Firstpage
    1649
  • Lastpage
    1660
  • Abstract
    Subband decomposition techniques have been extensively used for data coding and analysis. In most filter banks, the goal is to obtain subsampled signals corresponding to different spectral regions of the original data. However, this approach leads to various artifacts in images having spatially varying characteristics, such as images containing text, subtitles, or sharp edges. In this paper, adaptive filter banks with perfect reconstruction property are presented for such images. The filters of the decomposition structure which can be either linear or nonlinear vary according to the nature of the signal. This leads to improved image compression ratios. Simulation examples are presented
  • Keywords
    adaptive filters; adaptive signal processing; channel bank filters; data compression; filtering theory; image coding; image reconstruction; image sampling; prediction theory; adaptive filter banks; adaptive polyphase subband decomposition structures; adaptive prediction filters; data analysis; data coding; image artifacts; image compression ratios; linear filters; nonlinear filters; perfect reconstruction property; sharp edges; simulation; spatially varying characteristics; spectral regions; subsampled signals; subtitles; text; Adaptive filters; Data analysis; Filter bank; Finite impulse response filter; Frequency; Image analysis; Image coding; Image reconstruction; Signal processing; Video compression;
  • fLanguage
    English
  • Journal_Title
    Image Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1057-7149
  • Type

    jour

  • DOI
    10.1109/83.869176
  • Filename
    869176