预测三步搜索(PTSS)算法的运动估计

Hadi Amirpour, A. Mousavinia, Nakisa Shamsi
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引用次数: 10

摘要

运动估计是视频压缩中的一项重要任务,为了降低运动估计的计算复杂度,提出了许多算法。在传统的全搜索(FS)算法中,在搜索窗口中搜索所有块以寻找匹配项,与其他方法相比,产生非常可接受的PSNR。然而,它的计算开销很大。三步搜索(Three - Step Search, TSS)算法具有自适应限制搜索空间的优点,被广泛应用。本文提出的PTSS算法利用从相邻块中获得的运动信息,进一步减少了搜索块的数量。实验和仿真结果表明,与TSS相比,在相同或略有改善的PSNR下,速度提高了约20%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predictive Three Step Search (PTSS) algorithm for motion estimation
Motion estimation is a vital task in video compression and many algorithms are proposed to reduce its computational complexity. In a conventional Full Search (FS) algorithm, all blocks are searched for a match in the search window, resulting in a very acceptable PSNR compared to the other methods. However it suffers from heavy computational overhead. Three Step Search (TSS) algorithm which limits the search space adaptively, is used in many applications for its simplicity and effectiveness. The PTSS algorithm proposed in this paper decreases the number of search blocks even more, using motion information obtained from its neighboring blocks. Experimental and simulation results show approximately a 20% speed enhancement with the same or slightly improved PSNR in comparison to TSS.
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