• DocumentCode
    717686
  • Title

    Fast Distortion Estimation Based on Structural Similarity for H.264/SVC Encoded Videos

  • Author

    Babich, F. ; Comisso, M. ; Corrado, R.

  • Author_Institution
    Dept. of Eng. & Archit., Univ. of Trieste, Trieste, Italy
  • fYear
    2015
  • fDate
    11-14 May 2015
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Video quality assessments represent useful tools not only to evaluate the quality of the received video, but also to enable unequal error protection mechanisms. The computational cost of these quality assessments is however a relevant limitation to their use, mainly in the presence of time constraints, such as in live streaming applications. This paper proposes an algorithm capable to estimate, with a very low computational cost, the distortion due to the loss of a frame on videos encoded using the H.264 Scalable Video Coding (SVC) standard, by adopting one of the most reliable video quality assessments: the Structural SIMilarity (SSIM) index. The results show that the proposed solution allows one to obtain a satisfactory approximation of the exact SSIM-based distortion, simultaneously reducing the time required by the estimation process. The approximated SSIM distortion values are finally applied to an 802.11e distributed network with energy constraints, in order to test the effectiveness of the conceived algorithm in a practical scenario.
  • Keywords
    code standards; error correction codes; video coding; video streaming; wireless LAN; 802.11e distributed network; H.264 scalable video coding standard; SSIM-based distortion estimation; conceived algorithm; energy constraints; frame loss; structural similarity index; time constraint; unequal error protection mechanism; video encoding; video quality assessment; Approximation algorithms; Approximation methods; Distortion; Encoding; Estimation; IEEE 802.11e Standard; Videos;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Vehicular Technology Conference (VTC Spring), 2015 IEEE 81st
  • Conference_Location
    Glasgow
  • Type

    conf

  • DOI
    10.1109/VTCSpring.2015.7145840
  • Filename
    7145840