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Hybrid bitstream-based video quality assessment method for scalable video coding

机译:基于混合比特流的视频质量评估方法

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摘要

We propose a quality assessment method from decoding parameters of compressed bitstreams by scalable video coding (SVC) as a hybrid/bitstream category. Conventional video quality assessment methods evaluate the video quality of degraded videos after full reconstruction. However, the proposed assessment method quantifies video quality of SVC not only with reconstructed videos for the base layer but also with decoding parameters for the enhancement layer. The proposed algorithm assesses the enhanced quality degree of the enhancement layers with statistics of various coding parameters for the enhancement layers with respect to the quality of the base layer. The accuracy of the proposed algorithm is 23% higher than those of conventional algorithms in terms of Pearson correlation. Furthermore, the proposed algorithm has significantly lower computational complexity than conventional methods.
机译:我们提出了一种质量评估方法,该方法通过将可伸缩视频编码(SVC)作为混合/比特流类别来对压缩比特流的参数进行解码。常规视频质量评估方法在完全重建后评估降级视频的视频质量。然而,所提出的评估方法不仅利用针对基础层的重构视频而且利用针对增强层的解码参数来量化SVC的视频质量。所提出的算法利用相对于基础层的质量的针对增强层的各种编码参数的统计来评估增强层的增强质量等级。就皮尔逊相关性而言,所提出算法的准确性比传统算法高23%。此外,与传统方法相比,该算法的计算复杂度大大降低。

著录项

  • 来源
    《Optical Engineering》 |2012年第6期|p.1-9|共9页
  • 作者

    Seon-Oh Lee; Dong-Gyu Sim;

  • 作者单位

    Kwangwoon University, Department of Computer Engineering, 447-1, Wolgye-dong, Nowon-gu, Seoul 139-701, Republic of Korea;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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