Blind PSNR Estimation of Compressed Video Sequences Supported by Machine Learning

Takahiro Kumekawa, Masahiro Wakabayashi, Jiro Katto, Naofumi Wada

    研究成果: Article

    1 引用 (Scopus)

    抄録

    The peak signal-to-noise ratio (PSNR) used as an index of image quality usually requires original images, but this is difficult for consumer generated content such as videos on YouTube. Therefore, we developed two blind PSNR estimation methods without bit-stream analysis in which multiple support vector machines are prepared to learn differently encoded images in PSNR; using an entire frame and dividing the frame into two areas. We confirmed that higher estimation accuracy is possible for the latter method against that using the entire frame.

    元の言語English
    ページ(範囲)353-361
    ページ数9
    ジャーナルITE Transactions on Media Technology and Applications
    2
    発行部数4
    出版物ステータスPublished - 2014

    Fingerprint

    Learning systems
    Signal to noise ratio
    Image quality
    Support vector machines

    ASJC Scopus subject areas

    • Computer Graphics and Computer-Aided Design
    • Signal Processing
    • Media Technology

    これを引用

    Blind PSNR Estimation of Compressed Video Sequences Supported by Machine Learning. / Kumekawa, Takahiro; Wakabayashi, Masahiro; Katto, Jiro; Wada, Naofumi.

    :: ITE Transactions on Media Technology and Applications, 巻 2, 番号 4, 2014, p. 353-361.

    研究成果: Article

    Kumekawa, Takahiro ; Wakabayashi, Masahiro ; Katto, Jiro ; Wada, Naofumi. / Blind PSNR Estimation of Compressed Video Sequences Supported by Machine Learning. :: ITE Transactions on Media Technology and Applications. 2014 ; 巻 2, 番号 4. pp. 353-361.
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