提出一种利用特征跟踪进行电子稳像的算法,该算法具有计算量小,精度高,有鲁棒性等优点。算法由两部分构成:(1)基于特征点集二维运动模型进行全局运动估计。提取图像的特征点,以其为中心建立特征窗进行块匹配,得到匹配特征点集,根据特征点集内具有稳定相对位置的结构特征,提出距离不变准则,对特征匹配进行验证,以保证各点的局部运动具有良好的全局一致性,从而形成特征点集的全局运动矢量;(2)利用自适应均值滤波去除摄像机抖动。均值滤波器可以有效平滑摄像机的高频抖动,同时滤波器尺寸自适应地根据抖动频率来调整大小,能够防止过稳或欠稳。实验结果表明,该算法能够有效减轻摄像机的旋转和平移抖动。

A video stabilization algorithm is presented, which has the advantages of low computation cost, high accuracy and robustness. It consists of two parts: (1) global motion estimation is performed based on two-dimensional motion model of feature points set. The feature window with each selected feature point as the center is matched and then the corresponding points are obtained. The feature set has a stable structure, and the relative positions of all points are stable. So distance invariant criterion is proposed to check the feature matching, keep global coherence of all local motions and produce the global motion vector of the feature points; (2) a self-adaptive average filtering is applied to exclude the influence of the camera dithering. The average filter can smooth out the high frequency dithering effectively and adjust the window length automatically according to dithering frequency to prevent overstabilization or understabilization. Experimental results show that the algorithm can effectively reduce the influence of unwanted camera rotation and translation dithering.