Fast full search based block matching algorithm from fast kick-off of impossible candidate checking points

Jong-Nam Kim, Sung-Cheal Byun, Byung-Ha Ahn
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引用次数: 0

Abstract

To reduce an amount of computation of full search (FS) algorithm for fast motion estimation, we propose a new and fast matching algorithm without any degradation of predicted images like the conventional FS. The computational reduction without any degradation in predicted image comes from fast kick-off of impossible motion vectors. The fast kick-off of improper motion vectors comes from sequential rejection with derived formula and subblock norms. The sequential rejection of impossible candidates is based on multiple decision boundaries. Our proposed algorithm reduces more the computations than the recent fast full search (FS) motion estimation algorithms.
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基于不可能候选检查点快速启动的快速全搜索块匹配算法
为了减少全搜索(FS)算法在快速运动估计中的计算量,我们提出了一种新的快速匹配算法,而不像传统的FS那样对预测图像有任何退化。对不可能的运动向量进行快速启动,使预测图像的计算量减少而不出现任何退化。通过推导出的公式和子块范数进行序贯抑制,可以快速启动异常运动向量。顺序拒绝不可能的候选人是基于多个决策边界。该算法比现有的快速全搜索运动估计算法减少了更多的计算量。
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