视频抖动矫正中全局运动参数的估计

手持式终端拍摄视频时因为人手的抖动会出现画面不稳定现象。为稳定视频画面,提高视频的主观质量,提出了一种视频抖动矫正算法。该算法采用圆形块匹配获得当前帧像素的局部运动矢量。用迭代最小二乘法求解使用局部运动矢量和运动模型建立的线性参数系统获得全局平移、旋转及缩放运动参数。最后用运动迭代使运动参数更加精确。实验结果表明:该算法对平移、旋转及缩放运动的处理能力分别为大于30像素、大于30°及0.85~1.14,参数估计精度分别达到0.05像素、0.01°及0.0001,能处理的运动幅度范围以及运动参数的估计精度都比基于光流的算法均有很大提高。

Global motion estimation for video stabilization

Video sequences captured by handset are generally shaky.A video stabilization scheme developed to stabilize the video sequence and improve its visual quality uses circular block motion search to obtain the local motion vectors of pixels in the current frame.Then a linear system is constructed from these local motion vectors and solved to determine the global motion parameters which are refined by the motion iteration process.Experimental results show that the algorithm can estimate translational motions larger than 30 pixels,rotational motions larger than 30 degrees,and scaling motions between 0.85 and 1.14.The estimation precisions of these three motions are 0.05 pixels,0.01 degree,and 0.000 1,respectively.The algorithm not only deals with larger translational,rotational, and scaling motions than optical flow-based methods,but also achieves higher estimation precisions.