• DocumentCode
    454933
  • Title

    Adaptive Mad Prediction and Refined R-Q Model for H.264/AVC Rate Control

  • Author

    Liu, Y. ; Li, Z.G. ; Soh, Y.C.

  • Author_Institution
    Centre for Modeling & Control of Complex Syst., Nanyang Technol. Univ.
  • Volume
    2
  • fYear
    2006
  • fDate
    14-19 May 2006
  • Abstract
    This paper presents an improved rate control scheme for the H.264/AVC video coding scheme. By analyzing the relationship between direct mean absolute difference (MAD) and actual MAD, a new MAD prediction scheme is introduced to enhance traditional linear MAD prediction model, which is unable to predict abrupt MAD fluctuations. Our proposed adaptive model could reduce MAD prediction error by up to 34%. One simple sum bit quadratic R-Q model is also presented to solve the problem caused by inaccurate texture bits estimation of H.264/AVC. With the new MAD prediction model and R-Q model, our proposed scheme could reduce the mismatch between actual frame bits and target frame bits by up to 32%, and the buffer occupancy is much closer to the ideal status. Meanwhile, reconstructed video quality is also improved by up to 0.21 dB at low bitrate
  • Keywords
    image reconstruction; image texture; video coding; H.264/AVC rate control; adaptive MAD prediction; mean absolute difference; reconstructed video quality; refined RQ model; texture bits estimation; video coding scheme; Adaptive control; Automatic voltage control; Motion compensation; Motion estimation; Predictive models; Programmable control; Quadratic programming; Quantization; Video coding; Video compression;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on
  • Conference_Location
    Toulouse
  • ISSN
    1520-6149
  • Print_ISBN
    1-4244-0469-X
  • Type

    conf

  • DOI
    10.1109/ICASSP.2006.1660490
  • Filename
    1660490