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Content-based bitrate model for perceived compression distortion evaluation of mobile video services

机译:基于内容的比特率模型,用于评估移动视频服务的压缩失真

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摘要

A novel bitrate model with low complexity is proposed for perceived compression distortion assessment of mobile video with low resolution, which is extremely useful in intermediate network nodes for quality monitoring. Without fully decoding, parameters are extracted by bitstream analysing, such as bitrate, frame type, quantisation parameter, DCT coefficient, motion vector. Bitrate is regarded as an essential parameter meanwhile the bitrate-MOS curve is determined by video content. Respectively, spatial factor is estimated using quantisation parameter and DCT coefficient and temporal factor is estimated using motion vector. Apart from bitrate, the spatial and temporal factors, which reflect the characteristic of video content, are considered in the proposed model to obtain a more accurate evaluation. Experimental results show that the overall performance of proposed model significantly outperforms that of the other five bitrate models in terms of widely used performance criteria, including the Pearson correlation coefficient (PCC), the Spearman rank-order correlation coefficient (SROCC), the root-mean-squared error (RMSE) and the outlier ratio (OR).
机译:提出了一种低复杂度的新型比特率模型,用于低分辨率移动视频的感知压缩失真评估,这在中间网络节点进行质量监控时非常有用。如果没有完全解码,则通过比特流分析来提取参数,例如比特率,帧类型,量化参数,DCT系数,运动矢量。比特率被视为基本参数,而比特率-MOS曲线则取决于视频内容。分别使用量化参数和DCT系数估计空间因子,并使用运动矢量估计时间因子。除了比特率,在模型中还考虑了反映视频内容特征的时空因素,以获得更准确的评估。实验结果表明,就广泛使用的性能标准(包括皮尔逊相关系数(PCC),斯皮尔曼等级顺序相关系数(SROCC),根源和根源)而言,所提模型的整体性能明显优于其他五个比特率模型均方误差(RMSE)和离群值比(OR)。

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