• DocumentCode
    180278
  • Title

    SSIM-based rate-distortion optimization in H.264

  • Author

    Wei Dai ; Au, Oscar C. ; Wenjing Zhu ; Pengfei Wan ; Wei Hu ; Jiantao Zhou

  • Author_Institution
    Hong Kong Univ. of Sci. & Technol., Hong Kong, China
  • fYear
    2014
  • fDate
    4-9 May 2014
  • Firstpage
    7343
  • Lastpage
    7347
  • Abstract
    In the current video coding standards, rate-distortion optimization (RDO) plays an important role in achieving best tradeoff between the perceived distortion and transmission rate. It is widely used in all kinds of encoder decisions, including block mode decision, motion vector selection and so on. Generally, the sum of absolute difference (SAD) or the sum of square difference (SSD) is used as the distortion measurement. However, it is well known that both of them cannot always reflect the perceptual quality of the encoded video. In this paper, an objective quality measurement structural similarity (SSIM) index is proposed as the distortion measurement in the RDO framework for video coding standards. By fully exploiting the relationship between SSIM and mean square error (MSE), the SSIM-based RDO framework can be approximated by the original SSD-based RDO framework with only a scaling of the Lagrange multiplier. Experimental results show that the proposed method outperforms the latest H.264 codec and also the state-of-the-art SSIM-based RDO video codec.
  • Keywords
    mean square error methods; video coding; H.264 video coding standard; Lagrange multiplier; SSIM based rate distortion optimization; distortion measurement; encoder decision; mean square error method; objective quality measurement; perceived distortion; structural similarity index; transmission rate; Decision support systems; Distortion measurement; Indexes; Rate-distortion; Signal processing algorithms; Software algorithms; Video coding; SSIM; rate-distortion optimization; video coding;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
  • Conference_Location
    Florence
  • Type

    conf

  • DOI
    10.1109/ICASSP.2014.6855026
  • Filename
    6855026