• DocumentCode
    1876986
  • Title

    Accurate parameter estimation and efficient fade detection for weighted prediction in H.264 video compression

  • Author

    Zhang, Rui ; Cote, Guy

  • Author_Institution
    Cisco Syst. Inc, San Jose, CA
  • fYear
    2008
  • fDate
    12-15 Oct. 2008
  • Firstpage
    2836
  • Lastpage
    2839
  • Abstract
    Weighted prediction is a useful tool in video compression to encode scenes with lighting changes, such as fading scenes. Estimating weighted prediction parameters has been extensively discussed in the literature, however no mathematical model has been proposed. Moreover, the detection of the fading scenes in a real-time encoding system has received little attention. This paper addresses both of these aspects. An accurate parameter estimation algorithm for H.264 encoding is first derived for both the multiplicative factor and the additive offset based on a fading model. An efficient algorithm is then proposed to detect fade in a real-time encoding system, with simple statistics calculations, very low storage requirement, and low encoding delay. Simulation results show very accurate detection and compression gains of 5-30% over existing techniques.
  • Keywords
    data compression; parameter estimation; real-time systems; signal detection; video coding; H.264 video compression; accurate parameter estimation; fading scene detection; multiplicative factor; real-time encoding; scene encoding; statistics calculations; weighted prediction; Delay; Encoding; Fading; Layout; Mathematical model; Parameter estimation; Real time systems; Robustness; Statistics; Video compression; H.264; Weighted prediction; fade detection; video compression;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 2008. ICIP 2008. 15th IEEE International Conference on
  • Conference_Location
    San Diego, CA
  • ISSN
    1522-4880
  • Print_ISBN
    978-1-4244-1765-0
  • Electronic_ISBN
    1522-4880
  • Type

    conf

  • DOI
    10.1109/ICIP.2008.4712385
  • Filename
    4712385