Adaptively asymmetric pattern search for fast block-matching motion estimation

Tyng-Yeu Liang, Po-Hsien Kuo
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引用次数: 2

Abstract

In this paper, we invent a novel fast block-matching algorithm (BMA) for motion estimation (ME), called adaptively asymmetric pattern search (AAPS). Different to the other BMAs, this algorithm uses an asymmetrical search pattern and a predicted vector at the first search step, and dynamically adjusts the size of search pattern to minimize the number of search points. We have already applied AAPS to the process of motion estimation in the MPEG-4 encoding platform, and compared this algorithm with the other BMAs. The experimental result shows that AAPS achieves a 56-65% and 20% improvement in search speed respectively compared to the diamond search algorithm and the adaptive rood pattern search algorithm, and simultaneously maintains a high PSNR.
自适应非对称模式搜索快速块匹配运动估计
在本文中,我们发明了一种新的快速块匹配算法(BMA),称为自适应非对称模式搜索(AAPS)。与其他BMAs不同的是,该算法在第一步搜索时采用非对称搜索模式和预测向量,并动态调整搜索模式的大小以最小化搜索点的数量。我们已经将AAPS算法应用到MPEG-4编码平台的运动估计过程中,并与其他BMAs算法进行了比较。实验结果表明,与钻石搜索算法和自适应道路模式搜索算法相比,AAPS算法的搜索速度分别提高了56-65%和20%,同时保持了较高的PSNR。
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