基于曲线拟合的视频稳像方法

Video Image Stabilization Method Based on Curve Fitting

根据人眼的视觉特性,提出一种基于曲线拟合的视频稳像方法。使用图像背景特征点对摄像机的全局运动进行估计,利用曲线拟合的方法计算出摄像机的抖动分量,并将曲线拟合的结果作为摄像机的主观运动方向,对其摄像机的抖动运动分量进行补偿,使图像位移矢量达到最小,以有效减少运动补偿后引起的图像信息丢失。对抖动角度在20°内移动摄像机拍摄的视频进行稳像处理,实验结果表明,该方法稳像后视频的抖动角度小于2°,视频图像信息的损失小于5%,具有较好的稳像效果,并且在稳像后保证了视频帧内容的完整性。

According to the characteristics of the human visual, this paper presents a video image stabilization method that calculating the jittering component of the camera motion based on the curve fitting method, and does compensate to the jittering component. Global camera motion is estimated by using feature points of the image background. The jittering component of the camera is computed by curve fitting method. It only does jittering compensation in order to minimize the image displacement vector and effectively decrease the lost image information. Experimental results show that the jittering component is less 2 degree after stabilization, when the original video captured by moving camera is within 20 degree. And the loss of image information is less than 5%. As a result this method is effective, and better to retain the integrity of the content of the video frame after image stabilization.