• DocumentCode
    2594711
  • Title

    A fast mode decision method for intra prediction in AVS-M video coding

  • Author

    Zujue, Chen ; Jianchun, Bian ; Zhiwei, Feng

  • Author_Institution
    Dept. of Comput. Sci. & Telecommun. Eng., Jiangsu Univ., Zhenjiang, China
  • fYear
    2009
  • fDate
    18-20 Oct. 2009
  • Firstpage
    719
  • Lastpage
    723
  • Abstract
    A new method is put forward to decrease the high computational complexity during choosing the most suitable predicting mode in intra-prediction of AVS-M. In-depth studying the fast mode decision algorithm for intra prediction and characteristics of image pixels, the gray entropy is used to describe the feature of gray values in 4 times 4 block. For determining the candidate modes, the simple SAD function is presented to calculate the sampling points selected by gray entropy in the block. Then only candidate modes will be calculated in RDO function which can achieve the fast mode decision for intra prediction. Simulation results show that the algorithm can decrease 25%-33% of the total time in entire intra coding while maintaining PSNR and bit rate almost unchanged.
  • Keywords
    computational complexity; decision theory; entropy codes; feature extraction; image sampling; rate distortion theory; video coding; AVS-M video coding intra prediction; PSNR; RDO function; SAD function; bit rate; candidate mode; computational complexity; fast mode decision method; gray entropy; image pixel; rate distortion optimization; sampling point; sum-of-absolute difference; Automatic voltage control; Computational complexity; Computer science; Entropy; Image coding; Image sampling; Pixel; Space technology; Technology forecasting; Video coding; AVS-M; gray entropy; intra prediction; mode decision; sample;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Broadband Network & Multimedia Technology, 2009. IC-BNMT '09. 2nd IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-4590-5
  • Electronic_ISBN
    978-1-4244-4591-2
  • Type

    conf

  • DOI
    10.1109/ICBNMT.2009.5347776
  • Filename
    5347776