• DocumentCode
    1433284
  • Title

    H.264/SVC Mode Decision Based on Optimal Stopping Theory

  • Author

    Zhao, Tiesong ; Kwong, Sam ; Wang, Hanli ; Kuo, C. -C Jay

  • Author_Institution
    Dept. of Comput. Sci., City Univ. of Hong Kong, Kowloon, China
  • Volume
    21
  • Issue
    5
  • fYear
    2012
  • fDate
    5/1/2012 12:00:00 AM
  • Firstpage
    2607
  • Lastpage
    2618
  • Abstract
    Fast mode decision algorithms have been widely used in the video encoder implementation to reduce encoding complexity yet without much sacrifice in the coding performance. Optimal stopping theory, which addresses early termination for a generic class of decision problems, is adopted in this paper to achieve fast mode decision for the H.264/Scalable Video Coding standard. A constrained model is developed with optimal stopping, and the solutions to this model are employed to initialize the candidate mode list and predict the early termination. Comprehensive simulation results are conducted to demonstrate that the proposed method strikes a good balance between low encoding complexity and high coding efficiency.
  • Keywords
    computational complexity; video codecs; video coding; H.264/SVC mode decision; H.264/scalable video coding standard; coding efficiency; comprehensive simulation; encoding complexity; fast mode decision algorithms; optimal stopping theory; video encoder; Educational institutions; Encoding; Indexes; Prediction algorithms; Random variables; Scalability; Static VAr compensators; All-zero block (AZB) detection; interlayer prediction; mode decision; optimal stopping; scalable video coding (SVC); Algorithms; Data Compression; Image Enhancement; Image Interpretation, Computer-Assisted; Photography; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Video Recording;
  • fLanguage
    English
  • Journal_Title
    Image Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1057-7149
  • Type

    jour

  • DOI
    10.1109/TIP.2012.2186148
  • Filename
    6140970