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A new predictive search area approach for fast block motion estimation

机译:一种新的预测搜索区域方法,用于快速块运动估计

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According to the observation on the distribution of motion differentials among the motion vector of any block and those of its four neighboring blocks from six real video sequences, this paper presents a new predictive search area approach for fast block motion estimation. Employing our proposed simple predictive search area approach into the full search (FS) algorithm, our improved FS algorithm leads to 93.83% average execution-time improvement ratio, but only has a small estimation accuracy degradation. We also investigate the advantages of computation and estimation accuracy of our improved FS algorithm when compared to the edge-based search algorithm of Chan and Siu (see IEEE Trans. Image Processing, vol.10, p.1223-1238, Aug. 2001); experimental results reveal that our improved FS algorithm has 74.33% average execution-time improvement ratio and has a higher estimation accuracy. Finally, we further compare the performance among our improved FS algorithm, the three-step search algorithm, and the block-based gradient descent search algorithm.
机译:根据对来自六个真实视频序列的任何块的运动矢量及其四个相邻块的运动矢量之间运动差异分布的观察,本文提出了一种新的预测搜索区域方法,用于快速块运动估计。将我们提出的简单预测搜索区域方法应用于全搜索(FS)算法中,我们改进的FS算法可实现93.83%的平均执行时间改进率,但估计精度下降幅度很小。与Chan和Siu的基于边缘的搜索算法相比,我们还研究了改进的FS算法的计算和估计精度的优势(请参阅IEEE Trans。Image Processing,第10卷,第1223-1238页,2001年8月) ;实验结果表明,改进后的FS算法平均执行时间改进率为74.33%,估计精度更高。最后,我们进一步比较了改进的FS算法,三步搜索算法和基于块的梯度下降搜索算法的性能。

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