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A center-biased adaptive search algorithm for block motionestimation

机译:一种用于块运动估计的中心偏置自适应搜索算法

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摘要

A number of sub-optimal, but faster, search algorithms have been proposed in the literature, in order to alleviate the complexity associated with motion estimation by the full-search method. A new sub-optimal center-biased adaptive search algorithm for motion estimation is proposed; we refer to this algorithm as center-biased dynamic MInima Bounded Area Search (MIBAS) algorithm. The novelty of MIBAS is the checking point pattern at each subsequent step, composed of points lying in the area bounded by two local minima found at the present step, rather than points lying in a small neighborhood around a local minimum. The simulation results show that, compared to other fast algorithms, the center-biased MIBAS is more robust and produces smaller prediction errors and more reliable motion vectors, while it has a comparable computational complexity
机译:为了减轻与通过全搜索方法进行的运动估计有关的复杂性,文献中提出了许多次优但较快的搜索算法。提出了一种用于运动估计的次优中心偏置自适应搜索算法。我们将此算法称为偏心动态MInima边界区域搜索(MIBAS)算法。 MIBAS的新颖之处在于每个后续步骤中的检查点模式,它由位于当前步骤中找到的两个局部最小值所包围的区域中的点组成,而不是位于局部最小值附近的小邻域中的点组成。仿真结果表明,与其他快速算法相比,中心偏置的MIBAS具有更强的鲁棒性,并产生较小的预测误差和更可靠的运动矢量,同时具有相当的计算复杂性。

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