• DocumentCode
    3354333
  • Title

    Probability-based coding mode prediction for H.264/AVC

  • Author

    Zhao, Tiesong ; Wang, Hanli ; Kwong, Sam ; Hu, Sudeng

  • Author_Institution
    Dept. of Comput. Sci., City Univ. of Hong Kong, Hong Kong, China
  • fYear
    2010
  • fDate
    26-29 Sept. 2010
  • Firstpage
    3389
  • Lastpage
    3392
  • Abstract
    Fast mode decision (FMD) algorithm aims to reduce the computational complexity of video encoders, especially for H.264/AVC, and meanwhile keep the coding efficiency. It is necessary for coding high resolution sequences, such as standard definition (SD) or high definition (HD) sequences. In this paper, an efficient algorithm is proposed to speed up inter-mode decision for H.264/AVC. Firstly, for a macroblock (MB) being coded, with modes of neighboring blocks, a probability model is utilized to build up an optimal encoding mode list; after that, rate-distortion (RD) cost-based early termination is employed to skip unnecessary inter-modes. Simulation results demonstrate that, the proposed algorithm could achieve significant encoding time saving for QCIF/CIF and SD/HD sequences, meanwhile with almost the same RD performance as the original encoder.
  • Keywords
    probability; video coding; H.264/AVC; computational complexity; fast mode decision algorithm; intermode decision; macroblock; optimal encoding mode list; probability based coding mode prediction; probability model; rate distortion cost based early termination; video encoder; Automatic voltage control; Encoding; High definition video; Image coding; Prediction algorithms; Software; Video sequences; H.264/AVC; mode decision; neighboring prediction; probability model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2010 17th IEEE International Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1522-4880
  • Print_ISBN
    978-1-4244-7992-4
  • Electronic_ISBN
    1522-4880
  • Type

    conf

  • DOI
    10.1109/ICIP.2010.5652737
  • Filename
    5652737