• DocumentCode
    3514543
  • Title

    A new perceptual quality metric for compressed video

  • Author

    Bhat, Abharana ; Richardson, Iain ; Kannangara, Sampath

  • Author_Institution
    Robert Gordon Univ., Aberdeen
  • fYear
    2009
  • fDate
    19-24 April 2009
  • Firstpage
    933
  • Lastpage
    936
  • Abstract
    This paper presents a new video quality metric for automatically estimating the perceptual quality of compressed video sequences. Distortion measures such as the mean squared error (MSE) and the peak signal to noise ratio (PSNR) have been found to poorly correlate with visual quality at lower bit-rates. The proposed quality metric (MOSp) predicts perceptual quality of compressed video using sequence characteristics and the mean squared error (MSE) between the original and compressed video sequences. The metric has been tested on various video sequences compressed using the H.264 video compression standard at different bit-rates. Results show that the proposed metric has better correlation with subjective quality compared to popular metrics such as PSNR, SSIM and PSNRplus. The new metric is simple to compute and hence suitable for incorporation into real-time applications such as the standard video compression codecs inorder to improve the visual quality of compressed video sequences.
  • Keywords
    code standards; correlation methods; data compression; distortion; image sequences; mean square error methods; video coding; H.264 standard; compressed video sequence; correlation method; distortion measure; mean squared error; perceptual video quality metric; Code standards; Codecs; Distortion measurement; Humans; Noise measurement; PSNR; Testing; Video compression; Video sequences; Visual system; compressed video; mean squared error; perceptual quality; quality metrics; video quality;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on
  • Conference_Location
    Taipei
  • ISSN
    1520-6149
  • Print_ISBN
    978-1-4244-2353-8
  • Electronic_ISBN
    1520-6149
  • Type

    conf

  • DOI
    10.1109/ICASSP.2009.4959738
  • Filename
    4959738