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Low-Complexity Context-Based Motion Compensation for VLBR Video Encoding

机译:VLBR视频编码的基于低复杂度上下文的运动补偿

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摘要

A significant improvement of block-based motion estimation strategies is presented, which provides fast computation and very low bitrate coding. For each block, a spatio-temporal context is defined based on nearest neighbors in the current and previous frames, and a prediction list is built. Then, the best matching vector within the list is chosen as an estimation of the block motion. Since coder and decoder are synchronous, only the index of the selected vector is needed at the decoder to reconstruct the motion field. To avoid the propagation of the error, an additional correction vector can be sent when prediction error exceeds a threshold. Furthermore, bitrate saving is achieved through an adaptive sorting of the prediction list of each block, which allows to reduce the entropy of the motion indexes. Tests demonstrate that the proposed method ensures a speed up over 1:200 as compared to full search, and a coding gain above 2, with a negligible loss of accuracy. This allows real-time implementation of VLBR software video coders on conventional PC platforms.
机译:提出了基于块的运动估计策略的显着改进,其提供了快速计算和非常低的比特率编码。对于每个块,基于当前帧和先前帧中的最近邻居定义时空上下文,并构建预测列表。然后,选择列表中最佳匹配的向量作为块运动的估计。由于编码器和解码器是同步的,因此在解码器上只需要选定向量的索引即可重建运动场。为了避免误差的传播,当预测误差超过阈值时可以发送附加的校正向量。此外,通过对每个块的预测列表进行自适应排序,可以节省比特率,从而可以减少运动索引的熵。测试表明,与全搜索相比,该方法可确保速度提高1:200以上,并且编码增益大于2,而精度损失可忽略不计。这允许在常规PC平台上实时实施VLBR软件视频编码器。

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