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A ROBUST INTERPOLATION-FREE APPROACH FOR SUB-PIXEL ACCURACY MOTION ESTIMATION

机译:用于子像素精度运动估计的鲁棒的插值方法

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Motion estimation (ME) is one of the key elements in video coding standard which eliminates the temporal redundancy by using a motion vector (MV) to indicate the best match between the current frame and reference frame. A coarse to fine process is taken to find the best MV. First of all, integer-pixel ME finds a coarse MV and followed by the sub-pixel ME around the best integer-pixel point. The sub-pixel ME plays an important role in improving the coding efficiency. However, the computational complexity of searching one sub-pixel point is much higher than the integer-pixel point searching because of the interpolation and Hadamard transform operation. In this paper, an accurate optimal sub-pixel position prediction algorithm is presented. With the information of the 8 neighboring integer-pixel points, the optimal sub-pixel position is predicted directly without explicitly solving model parameters. Moreover, an outlier rejection scheme is applied to improve the robustness of the proposed algorithm. Experimental results show that the proposed algorithm outperforms the state of the art interpolation-free sub-pixel ME algorithms.
机译:运动估计(ME)是视频编码标准中的关键元件之一,其通过使用运动矢量(MV)来消除时间冗余,以指示当前帧和参考帧之间的最佳匹配。粗糙到精细的过程是为了找到最好的mv。首先,整数像素我发现了一个粗略的MV,然后是最佳整数像素点周围的子像素。子像素我在提高编码效率方面发挥着重要作用。然而,由于插值和Hadamard变换操作,搜索一个子像素点的计算复杂度远高于整数像素点搜索。本文介绍了一种精确的最佳子像素位置预测算法。利用8个相邻整数像素点的信息,直接预测最佳子像素位置而不明确地解决模型参数。此外,应用了异常值抑制方案来提高所提出的算法的鲁棒性。实验结果表明,所提出的算法优于自由内插子像素ME算法的状态。

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