• DocumentCode
    3601280
  • Title

    No-Reference Video Quality Assessment Using Codec Analysis

  • Author

    Sogaard, Jacob ; Forchhammer, Soren ; Korhonen, Jari

  • Author_Institution
    Dept. of Photonics, Tech. Univ. of Denmark, Lyngby, Denmark
  • Volume
    25
  • Issue
    10
  • fYear
    2015
  • Firstpage
    1637
  • Lastpage
    1650
  • Abstract
    A no-reference (NR) video quality assessment (VQA) method is presented for videos distorted by H.264/Advanced Video Coding (AVC) and MPEG-2. The assessment is performed without access to the bitstream. Instead, we analyze and estimate coefficients based on decoded pixels. The approach involves distinguishing between the two types of videos, estimating the level of quantization used in the I-frames, and exploiting this information to assess the video quality. To do this for H.264/AVC, the distribution of the discrete cosine transform-coefficients after intra-prediction and deblocking are modeled. To obtain VQA features for H.264/AVC, we propose a novel estimation method of the quantization in H.264/AVC videos without bitstream access, which can also be used for peak signal-to-noise ratio estimation. The results from the MPEG-2 and H.264/AVC analysis are mapped to a perceptual measure of video quality by support vector regression. For validation purposes, the proposed method was tested on two databases. In both cases, a good performance compared with state of the art full, reduced, and NR VQA algorithms was achieved.
  • Keywords
    discrete cosine transforms; regression analysis; support vector machines; video coding; AVC; H.264/AVC analysis; H.264/advanced video coding; MPEG-2; VQA method; bitstream access; codec analysis; decoded pixels; discrete cosine transform coefficients; noreference video quality assessment; peak signal-to-noise ratio estimation; support vector regression; Codecs; Databases; Estimation; PSNR; Quantization (signal); Transform coding; Video coding; H264/Advanced Video Coding (AVC); no-reference (NR); peak signal-to-noise ratio (PSNR) estimation; pixel-based (PB); video codec analysis; video quality assessment (VQA);
  • fLanguage
    English
  • Journal_Title
    Circuits and Systems for Video Technology, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1051-8215
  • Type

    jour

  • DOI
    10.1109/TCSVT.2015.2397207
  • Filename
    7029632