Girod B
Dept. of Electr. Eng., Stanford Univ., CA 94305, USA.
IEEE Trans Image Process. 2000;9(2):173-83. doi: 10.1109/83.821595.
Overlapped block motion compensation or B-frames are examples of multihypothesis motion compensation where several motion-compensated signals are superimposed to reduce the bit-rate of a video codec. This paper extends the wide-sense stationary theory of motion-compensated prediction (MCP) for hybrid video codecs to multihypothesis motion compensation. The power spectrum of the prediction error is related to the displacement error probability density functions (pdfs) of an arbitrary number of hypotheses in a closed-form expression. We then study the influence of motion compensation accuracy on the efficiency of multihypothesis motion compensation as well as the influence of the residual noise level and the gain from optimal combination of N hypotheses. For the noise-free limiting case, doubling the number of (equally good) hypotheses can yield a gain of up to 1/2 bits/sample, while doubling the accuracy of motion compensation can additionally reduce the bit-rate by up to 1 bit/sample independent of N. For realistic noise levels, it is shown that the introduction of B-frames or overlapped block motion compensation can provide larger gains than doubling motion compensation accuracy. Spatial filtering of the motion-compensated candidate signals becomes less important if more hypotheses are combined. The critical accuracy beyond which the gain due to more accurate motion compensation is small moves to larger displacement error variances with increasing noise and increasing number of hypotheses N. Hence, sub-pel accurate motion compensation becomes less important with multihypothesis MCP. The theoretical insights are confirmed by experimental results for overlapped block motion compensation, B-frames, and multiframe motion-compensated prediction with up to eight hypotheses from ten previous frames.
重叠块运动补偿或B帧是多假设运动补偿的示例，其中几个运动补偿信号被叠加以降低视频编解码器的比特率。本文将混合视频编解码器的运动补偿预测（MCP）广义平稳理论扩展到多假设运动补偿。预测误差的功率谱与任意数量假设的位移误差概率密度函数（pdf）以封闭形式表达式相关。然后，我们研究运动补偿精度对多假设运动补偿效率的影响，以及残余噪声水平和N个假设的最优组合增益的影响。对于无噪声极限情况，将（同样好的）假设数量加倍可产生高达1/2比特/样本的增益，而将运动补偿精度加倍可额外将比特率降低多达1比特/样本，与N无关。对于实际噪声水平，结果表明引入B帧或重叠块运动补偿可提供比将运动补偿精度加倍更大的增益。如果组合更多假设，运动补偿候选信号的空间滤波变得不那么重要。随着噪声增加和假设数量N增加，由于更精确运动补偿而产生的增益较小的临界精度会转移到更大的位移误差方差。因此，对于多假设MCP，亚像素精确运动补偿变得不那么重要。对于重叠块运动补偿、B帧以及来自十个先前帧的多达八个假设的多帧运动补偿预测的实验结果证实了这些理论见解。
