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Distance scaling of higher order motion parameters in an extension of HEVC

机译:高阶运动参数在HEVC的扩展中的距离缩放

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Complex motion in video sequences, such as rotation and scaling, conventionally approximated translationally, can more efficiently be represented by higher order motion models. An important contribution to the efficiency of the higher order motion compensation approach is the prediction and encoding of the additional motion parameters. The additional data rate caused by an increased amount of motion parameters has to be kept small for the higher order motion model to outperform the translational one within blocks of complex motion. Addressing an aspects of motion prediction yet to be adjusted to higher order motion, this paper proposes an advanced method of distance scaling of higher order motion parameters. Just as translational motion vector predictors require scaling whenever the block inheriting them has a different distance to its reference picture than the block predicted from, higher order motion parameter prediction can profit from such scaling as well. However, the distance scaling of higher order motion parameters cannot be applied to the elements of the motion model transformation matrix directly, but is performed on separate higher order motion components provided by a preceding transformation matrix decomposition. Accordingly, the objective of this work is to introduce and evaluate a procedure for higher order motion distance scaling. The resulting rate reduction of about 2% on average and up to over 6% attains a further improvement on the higher order motion compensation in an extension of HEVC.
机译:视频序列中的复杂运动,例如旋转和缩放,传统上近似于性地,可以更有效地由更高阶运动模型表示。对更高阶运动补偿方法的效率的重要贡献是预测和编码附加运动参数。由增加的运动参数量引起的附加数据速率必须为更高阶运动模型而保持小,以优于复杂运动块内的翻译。解决尚未调整到更高阶运动的运动预测的一个方面,本文提出了一种高阶运动参数的距离缩放方法的先进方法。正如翻译运动矢量预测器,只要将它们的块具有与其参考图片的块相比,就需要缩放而不是预测的块,也可以从这种缩放中获利更高阶运动参数预测。然而,高阶运动参数的距离缩放不能直接应用于运动模型变换矩阵的元件,而是在由前一个变换矩阵分解提供的单独的高阶运动组件上执行。因此,这项工作的目的是引入和评估更高阶运动距离缩放的过程。由此产生的速率平均约2%,高达6%以上达到了HEVC的延伸中更高阶运动补偿的进一步改进。

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