一种快速鲁棒的全局运动估计算法

局部运动矢量会严重影响全局运动估计的结果,不仅降低全局运动估计的准确度,而且消耗大量的运算时间。针对上述问题提出了一种快速鲁棒的全局运动估计算法。首先采用快速的块匹配算法得到运动矢量场,然后通过改进的梯度均值残差法去除估计的不准确运动矢量,提高估计出的运动矢量场的准确性并使得全局运动估计所处理的宏块尽可能是全局运动块;其次,基于六参数仿射模型估计出初始全局运动参数,为了消除错误运动矢量产生的误差,使用匹配加权函数的方法对估计结果进行进一步修正,最终得到最优的全局运动参数。实验结果表明该算法兼顾了全局运动估计的准确性和鲁棒性,对大多数视频序列的全局运动估计具有算法复杂度低、运动参数估计准确的效果。

A Fast and Robust Global Motion Estimation Algorithm

Local movement and inaccurate motion vectors affect the accuracy of global motion estimation seriously. In order to solve this problem, a fast and robust global motion estimation algorithm is proposed in this paper. Firstly, block matching algorithm (BMA) is used to estimate motion vectors. Then the inaccurate motion vectors are excluded by gradient mean residual error method to improve the accuracy of estimated global motion field. Secondly, the initial global motion parameters are estimated using a 6-parameter affine model and they are iteratively refined by matching weighting method. Thus the most accurate global motion parameters can be obtained. Experimental results show that the proposed method is efficient and robust in terms of both computational complexity and accuracy.