H.264/AVC中块运动估计的多方向搜索算法

C. C. Lin, Y. Lin, H. Hsieh
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引用次数: 19

摘要

针对块运动估计,提出了三步搜索、新三步搜索、四步搜索、基于块的梯度下降搜索、菱形搜索和基于六边形搜索等高效的搜索算法来搜索最优目标函数。块ME技术涉及到一个优化问题。虽然这些算法可以快速收敛到极小点,但如果目标函数有多个极小值,它们就会陷入局部极小值。为了解决这一问题,在H.264/AVC中提出了混合多六边形网格搜索(UMHexagonS)算法,该算法在较宽的搜索范围内采用非对称交叉搜索和不均匀的混合六边形网格搜索来寻找接近全局的最小值。实验表明,混合umhexagon算法计算量大,有时会陷入局部最小值。本文提出了一种新的快速搜索算法,即多方向搜索(multi-direction search, MDS)算法,该算法首先利用多方向搜索找到所有可能的局部最优点,然后利用扩展六边形搜索对这些点进行细化,得到最终的最优运动向量。实验结果表明,与混合UMHexagonS算法相比,在保持更好的编码性能的同时,可以实现显著的计算减少(对于MDS和快速MDS,平均搜索点减少约30%和50%,对应于总编码时间减少19%和37%)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-direction search algorithm for block motion estimation in H.264/AVC
Many efficient search algorithms such as three-step search, new three-step search, four-step search, block-based gradient descent search, diamond search and hexagon-based search are developed for block motion estimation (ME) to search for the optimal objective function. The block ME technique involves an optimisation problem. Although these algorithms can converge to a minimal point rapidly, they suffer from becoming trapped in local minimum if the objective function has multiple minima. To solve this problem, the hybrid multi-hexagon-grid search (UMHexagonS) algorithm has been proposed in H.264/AVC, in which an unsymmetrical-cross search and an uneven UMHexagonS are employed over a wide search range to find a nearly global minimum. The experiment shows that the hybrid UMHexagonS algorithm is computation expensive and is occasionally trapped in local minimum. The authors propose a novel and fast search algorithm, called multi-direction search (MDS) algorithm, which uses an MDS first to find all possible locally optimal points and then uses the extended hexagon search to refine these points for the final optimal motion vector. The experimental results indicate that a significant improvement in computation reduction (∼30 and 50% reduction in average search points, corresponding to 19 and 37% reduction in total encoding time, for MDS and fast MDS, respectively) can be achieved while maintaining better coding performance, compared with the hybrid UMHexagonS algorithm.
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