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Analysis of objective video quality metric using the wavelet transform

机译:用小波变换分析客观视频质量指标

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In this paper, we investigate the performance of an objective video quality assessment method using the wavelet transform for a large data set. The objective video quality assessment utilizes the wavelet transform, which is applied to each frame of source and processed videos in order to compute spatial frequency components. Then, the difference (squared error) of the wavelet coefficients in each subband is computed and summed. By repeating this procedure to the entire frames of a video, a sequence of difference vectors and the average vector are obtained. Each component of the average vector represents a difference in a certain spatial frequency. In order to take into account the temporal frequencies, a modified 3-D wavelet transform can be applied. Although this evaluation method provides a good performance for training data, its performance for new test videos remains to be seen due to a large number of parameters. In this paper, we apply the method to a large video data set and analyze the performance.
机译:在本文中,我们研究了使用小波变换进行大数据集的客观视频质量评估方法的性能。目标视频质量评估利用小波变换,该小波变换应用于源帧和处理的视频,以计算空间频率分量。然后,计算和求和每个子带中的小波系数的差值(平方误差)。通过将该过程重复到视频的整个帧,获得了一系列差值向量和平均向量。平均矢量的每个组件表示某个空间频率的差异。为了考虑时间频率,可以应用修改的3-D小波变换。虽然这种评估方法为训练数据提供了良好的性能,但由于大量参数,它对新测试视频的性能仍然可以看到。在本文中,我们将该方法应用于大型视频数据集并分析性能。

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