• DocumentCode
    1799562
  • Title

    Fast coding unit depth decision for HEVC

  • Author

    Fangshun Mu ; Li Song ; Xiaokang Yang ; Zhenyi Luo

  • Author_Institution
    Inst. of Image Commun. & Network Eng., Shanghai Jiao Tong Univ., Shanghai, China
  • fYear
    2014
  • fDate
    14-18 July 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    High Efficiency Video Coding (HEVC) achieves high efficiency by introducing a new coding structure in adoption of coding unit (CU), prediction unit (PU) and transform unit (TU). However, it also imposes great computation burden on the mode decision of encoders. In this paper, we propose a fast CU depth decision scheme to reduce the encoder complexity for HEVC. Firstly, the relationship between rate-distortion (R-D) cost and CU depth is explored carefully with Mean Squared Error (MSE) and Number of Encoded Bits (NEB) metrics. Then CU splitting is modeled as a binary classification problem and resolved by an offline trained Support Vector Machine (SVM) model. The experimental results show that the proposed algorithm achieves up to 59% running-time reduction with negligible loss in terms of PSNR and bit rate.
  • Keywords
    mean square error methods; rate distortion theory; support vector machines; video coding; HEVC; MSE; SVM; binary classification problem; coding unit depth decision; content adaptation; encoder complexity; high efficiency video coding; mean square error methods; mode decision; offline trained support vector machine; prediction unit; rate-distortion cost; transform unit; Bit rate; Classification algorithms; Educational institutions; Encoding; Prediction algorithms; Support vector machines; Video coding; Content adaptation; HEVC; Video coding and processing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia and Expo Workshops (ICMEW), 2014 IEEE International Conference on
  • Conference_Location
    Chengdu
  • ISSN
    1945-7871
  • Type

    conf

  • DOI
    10.1109/ICMEW.2014.6890647
  • Filename
    6890647