基于分块灰度投影的无人飞行器视频稳像方法

针对传统灰度投影算法局部运动影响全局运动矢量估计精度的问题,结合无人飞行器航摄视频图像的特点,提出一种适用于无人飞行器的视频稳像方法. 该方法将图像划分为若干子区域,剔除灰度特征不明显和物体局部运动等影响全局运动估计精度的子区域,对保留的子区域分别采用灰度投影法计算运动矢量,由局部运动估算出图像的全局运动矢量,经过运动决策,将运动补偿矢量应用于图像补偿,获得稳定的视频图像. 对真实无人飞行器航摄视频稳像实验结果表明,该算法稳像准确度与块匹配全搜索算法相当,而单帧稳像时间只有块匹配全搜索算法的1/3,在准确性和实时性方面均优于传统灰度投影算法. 

A UAV Video Stabilization Method Based on Sub-Block Gray Projection

Considering the characteristics of unmanned aerial vehicle(UAV) aerial video, a UAV video stabilization method based on sub-block projection is proposed, which improves the accuracy of global motion estimation. This method divides an image into several sub-blocks and wipes off those sub-blocks which contain local motions and are textureless in gray level. Then the motion vectors of the sub-blocks remained are calculated respectively by using gray projection algorithm. Further, the global motion vector is estimated by local motions. Finally, after the motion decision, the tremble motion vector is used for motion compensation. Experiments on real video images of UAV demonstrate that the accuracy of this method is close to the standard motion estimation algorithm, but the time consumption is only one third of it. The result also shows that the effectiveness and the efficiency of the proposed algorithm are superior to the traditional gray projection algorithm.