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Hybrid parallel motion estimation architecture based on fast top-winners search algorithm

机译:基于快速优胜者搜索算法的混合并行运动估计架构

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In this paper, a hybrid parallel motion estimation architecture based on the fast top-winners algorithm is proposed. In the first instance, the fast top-winners search algorithm is discussed based on the pel-subsampling technique to reduce the computational amount of the sum of absolute difference (SAD). Moreover, the four-parallel spiral scanning (4PSP) with the partial distortion elimination (PDE) mechanism is also utilized to early terminate the unnecessary SAD. Therefore, the proposed fast algorithm can not only avoid trapping into the problem of the local minimum but also save the computational operations with a little performance degradation. According to our proposed algorithm, the 4×4 processing element (PE) array and the dual mode SAD tree are proposed to efficiently perform SAD and Sub-SAD which is accumulated based on the pel-subsampling. For the sake of reducing the system memory bandwidth and decreasing the frequency of the memory access, the local memory configuration and the novel memory interleaving organization are proposed to arrange the current data and reference pixels easily, to access the image pixels efficiently, and to achieve the Level C (Lv. C) data reuse scheme.
机译:本文提出了一种基于快速优胜者算法的混合并行运动估计架构。首先,讨论了一种基于象素二次采样技术的快速优胜者搜索算法,以减少绝对差之和(SAD)的计算量。此外,具有部分失真消除(PDE)机制的四平行螺旋扫描(4PSP)也可用于尽早终止不必要的SAD。因此,所提出的快速算法不仅可以避免陷入局部极小值的问题,而且可以节省计算性能,并且性能下降很小。根据我们提出的算法,提出了4×4处理元件(PE)阵列和双模式SAD树,以有效地执行SAD和Sub-SAD,这些SAD和Sub-SAD是基于像素二次采样而累积的。为了减少系统内存带宽和减少内存访问的频率,提出了本地内存配置和新颖的内存交错组织,以方便地排列当前数据和参考像素,有效访问图像像素,并实现C级(Lv.C)数据重用方案。

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