• DocumentCode
    62659
  • Title

    Fast Mode Decision Algorithm for the H.264/AVC Scalable Video Coding Extension

  • Author

    Xin Lu ; Martin, Graham R.

  • Author_Institution
    Dept. of Comput. Sci., Univ. of Warwick, Coventry, UK
  • Volume
    23
  • Issue
    5
  • fYear
    2013
  • fDate
    May-13
  • Firstpage
    846
  • Lastpage
    855
  • Abstract
    A fast mode decision algorithm for efficient implementation of the scalable video coding (SVC) extension of H.264/AVC is described. SVC incorporates interlayer prediction, a new tool that exploits as much lower layer information as possible in order to improve the coding efficiency of the enhancement layer. However, it also greatly increases the computational complexity. A fast mode selection algorithm that exploits the correlation of a macroblock in the enhancement layer and both the colocated macroblocks in the base layer and neighboring macroblocks in the enhancement layer is proposed. The algorithm examines the level of picture details and motion activity, and utilizes the mode information of the base layer to make faster enhancement layer decisions and thus save coding time. Simulation results show that the proposed algorithm reduces encoding by up to 84% compared with the JSVM 9.18 implementation. This is achieved without any noticeable degradation in rate distortion.
  • Keywords
    computational complexity; data compression; video coding; H.264-AVC scalable video coding extension; JSVM 9.18 implementation; SVC extension; base layer; colocated macroblocks; computational complexity; enhancement layer; fast mode decision algorithm; mode information; motion activity; neighboring macroblocks; Accuracy; Correlation; Encoding; Prediction algorithms; Static VAr compensators; Video coding; Video sequences; Fast mode selection; SVC extension of H264/AVC; interlayer prediction; scalable video coding (SVC);
  • fLanguage
    English
  • Journal_Title
    Circuits and Systems for Video Technology, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1051-8215
  • Type

    jour

  • DOI
    10.1109/TCSVT.2012.2226525
  • Filename
    6340317