• DocumentCode
    3093593
  • Title

    Subjective Quality Optimized Intra Mode Selection for H.264 I Frame Coding Based on SSIM

  • Author

    Cui, Ziguan ; Zhu, Xiuchang

  • Author_Institution
    Image Process. & Image Commun. Lab., Nanjing Univ. of Posts & Telecommun., Nanjing, China
  • fYear
    2011
  • fDate
    12-15 Aug. 2011
  • Firstpage
    157
  • Lastpage
    162
  • Abstract
    H.264/AVC adopts rate distortion optimization (RDO) technique to select optimal macro block (MB) coding mode and achieves higher compression efficiency, but the traditional RDO framework employs pixel wise mean square error (MSE) and the like as objective distortion metric, which can not acquire optimal subjective quality. This paper applies structural similarity (SSIM) based subjective distortion to RDO-based intra mode decision in H.264 I frame coding, and further proposes a frame layer adaptive Lagrange multiplier adjustment scheme to get better tradeoff between rate and SSIM distortion. Experimental results show that, the proposed scheme encodes more image structural information and thus acquires better subjective quality and coding efficiency compared with MSE-based RDO method.
  • Keywords
    data compression; video coding; H.264 I frame coding; H.264-AVC; MSE; RDO technique; SSIM distortion; SSIM-based subjective distortion; compression efficiency; frame layer adaptive Lagrange multiplier adjustment scheme; image structural information; objective distortion metric; optimal macroblock coding mode; pixelwise mean square error; rate distortion optimization; structural similarity-based subjective distortion; subjective quality optimized intramode selection; Adaptation models; Bit rate; Encoding; Equations; Image coding; Indexes; Mathematical model; H.264; Lagrange multiplier; intra mode decision; structural similarity (SSIM);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image and Graphics (ICIG), 2011 Sixth International Conference on
  • Conference_Location
    Hefei, Anhui
  • Print_ISBN
    978-1-4577-1560-0
  • Electronic_ISBN
    978-0-7695-4541-7
  • Type

    conf

  • DOI
    10.1109/ICIG.2011.13
  • Filename
    6005568