摘要
为了提高自适应十字搜索(adaptive rood pattern search,ARPS)算法中运动估计的速度和准确性,提出一种基于空间相关预测的快速块匹配运动估计算法.根据块匹配度量准则,将邻域块中与当前块相似度最高和次高的两个运动向量(motion vector,MV)的均值作为当前块的预测MV,改进了传统ARPS算法的固定单块预测模式,增强了起始搜索中心位置的预测,减小了由于运动变化而引起的预测误差.实验结果表明所提算法与ARPS和其他标准快速块匹配运动估计方法相比,有效地减少了计算复杂度,提高了配准精度.
In order to improve the speed and accuracy of motion estimation in adaptive rood pattern search （ARPS）algorithm, a fast block matching motion estimation algorithm was proposed on the basis of spatial correlation prediction. According to the block matching metric, in the proposed algorithm, the motion vector （MV）of current block was predicted by computing mean MVs of the two blocks with higher similarity in the neighborhood blocks instead of the fixed single block prediction pattern in ARPS. The prediction performance of initial search center location was improved with the proposed algorithm, and the prediction error resulted from motion transformation was reduced. Experimental results demonstrated that the computational complexity could be effectively decreased, and the registration accuracy was increased as well in comparison to APRS and the other standard block matching algorithms.
出处
《东北大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2014年第4期470-473,488,共5页
Journal of Northeastern University(Natural Science)
基金
国家自然科学基金资助项目(61273078
61005032)
中央高校基本科研业务费专项资金资助项目(N110604006)
关键词
运动估计
视频编码
预测向量
空间相关
块匹配算法
motion estimation
video coding
prediction vector
spatial correlation
blockmatching algorithm
