• DocumentCode
    1969217
  • Title

    Reference free SSIM estimation for full HD video content

  • Author

    Ries, Michal ; Slanina, Martin ; Garcia, David Mora

  • Author_Institution
    Inst. of Telecommun., Univ. of Technol. Vienna, Vienna, Austria
  • fYear
    2011
  • fDate
    19-20 April 2011
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    This paper proposes a reference-free video quality estimation method for full high definition video services based on a structural similarity index. The design of our estimator is based on an artificial neural network. To achieve this, the neural network was trained with a set of video statistical parameters extracted from the most representative video contents. Moreover, estimations with neural networks allow higher applicability and require lower processing power as known reference based methods. Finally, the achieved correlation between the calculated and the estimated structural similarity index shows a very good fit.
  • Keywords
    high definition video; neural nets; statistical analysis; video signal processing; artificial neural network; full HD video content; full high definition video service; reference free SSIM estimation; reference-free video quality estimation; structural similarity index; video statistical parameter; Artificial neural networks; Estimation; High definition video; Indexes; Quantization; Streaming media; Training; Video quality; artificial neural network; high definition video service; structural similarity;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Radioelektronika (RADIOELEKTRONIKA), 2011 21st International Conference
  • Conference_Location
    Brno
  • Print_ISBN
    978-1-61284-325-4
  • Type

    conf

  • DOI
    10.1109/RADIOELEK.2011.5936447
  • Filename
    5936447