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Rate-distortion analysis of motion-compensated rate scalable video

机译:运动补偿速率可伸缩视频的速率失真分析

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Generally speaking, rate scalable video systems today are evaluated operationally, meaning that the algorithm is implemented and the rate-distortion performance is evaluated for an example set of inputs. However, in these cases it is difficult to separate the artifacts caused by the compression algorithm and data set with general trends associated with scalability. In this paper, we derive and evaluate theoretical rate-distortion performance bounds for both layered and continuously rate scalable video compression algorithms which use a single motion-compensated prediction (MCP) loop. These bounds are derived using rate-distortion theory based on an optimum mean-square error (MSE) quantizer, and are thus applicable to all methods of intraframe encoding which use MSE as a distortion measure. By specifying translatory motion and using an approximation of the predicted error frame power spectral density, it is possible to derive parametric versions of the rate-distortion functions which are based solely on the input power spectral density and the accuracy of the motion-compensated prediction. The theory is applicable to systems which allow prediction drift, such as the data-partitioning and SNR-scalability schemes in MPEG-2, as well as those with zero prediction drift such as fine granularity scalability MPEG-4. For systems which allow prediction drift we show that optimum motion compensation is a sufficient condition for stability of the decoding system.
机译:一般而言,当今的速率可伸缩视频系统是在操作上进行评估的,这意味着将对示例输入集实施该算法并评估速率失真性能。然而,在这些情况下,难以将由压缩算法和数据集引起的伪像与与可伸缩性相关的一般趋势分开。在本文中,我们推导并评估了使用单个运动补偿预测(MCP)循环的分层和连续速率可伸缩视频压缩算法的理论速率失真性能范围。这些范围是基于最佳均方误差(MSE)量化器使用率失真理论得出的,因此适用于使用MSE作为失真度量的所有帧内编码方法。通过指定平移运动并使用预测的误差帧功率谱密度的近似值,可以仅基于输入功率谱密度和运动补偿预测的精度来得出速率失真函数的参数版本。该理论适用于允许预测漂移的系统,例如MPEG-2中的数据分区和SNR可伸缩性方案,以及零预测漂移的系统,例如精细粒度可伸缩性MPEG-4。对于允许预测漂移的系统,我们表明最佳运动补偿是解码系统稳定性的充分条件。

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