No-Reference Video Quality Assessment Based on Artifact Measurement and Statistical Analysis

A DCT-based no-reference video quality prediction model is proposed that measures artifacts and analyzes the statistics of compressed natural videos. The model has two stages: distortion measurement and non-linear mapping. In the first stage, an unsigned AC band, three frequency bands, and two orientation bands are generated from the discrete cosine transform (DCT) coefficients of each decoded frame in a video sequence. Six efficient frame-level features are then extracted to quantify the distortion of natural scenes. In the second stage, each frame-level feature of all frames is transformed to a corresponding video-level feature via a temporal pooling, then a trained multilayer neural network takes all video-level features as inputs and outputs a score as the predicted quality of the video sequence. The proposed method was tested on videos with various compression types, content, and resolution in four databases. We compared our model with a linear model, a support-vectorregression based model, a state-of-the-art training-based model, and four popular full-reference metrics. Detailed experimental results demonstrate that the results of the proposed method are highly correlated with the subjective assessments.

Subject (DDC)

004 Computer Science

Keywords

Blocking artifact, DCT, H.264/AVC, natural scene, noreference measure, video quality assessment

Cite This

ISO 690

ZHU, Kongfeng, Changxiu LI, Vijayan ASARI, Dietmar SAUPE, 2015. No-Reference Video Quality Assessment Based on Artifact Measurement and Statistical Analysis. In: IEEE Transactions on Circuits and Systems for Video Technology. 25(4), pp. 533-546. ISSN 1051-8215. eISSN 1558-2205. Available under: doi: 10.1109/TCSVT.2014.2363737

BibTex

@article{Zhu2015NoRef-30710,
  year={2015},
  doi={10.1109/TCSVT.2014.2363737},
  title={No-Reference Video Quality Assessment Based on Artifact Measurement and Statistical Analysis},
  number={4},
  volume={25},
  issn={1051-8215},
  journal={IEEE Transactions on Circuits and Systems for Video Technology},
  pages={533--546},
  author={Zhu, Kongfeng and Li, Changxiu and Asari, Vijayan and Saupe, Dietmar}
}

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Bibliography of Konstanz

Yes