应用于稳像系统中的改进梯度光流法

Improved gradient optical flow for digital image stabilization

由于传统的梯度光流法当运动不连续时运动场估计值与真实值有较大偏差,因而不能直接应用于稳像系统中。引入金字塔多分辨率分层技术对传统的梯度光流法进行改进。首先,在视频序列中选定细节丰富的区域作为计算区域;其次,利用结合金字塔多分辨率分层技术的光流法迭代求解相邻帧间的仿射参数;最后,采用帧间补偿方式,并增加控制累积错误传播的措施,在不丢失过多原有信息基础上,实现了长时间稳像。实验表明:改进的方法能够检测出剧烈的复杂抖动,并能达到旋转精度小于0.09°、平移精度小于0.07个像素,缩放精度小于0.02的高精度估计,且补偿序列平均峰值信噪比值提高了2.36 d B以上。

Traditional gradient optical flow has large motion estimation deviation with real value, thus cannot be directly applied to image stabilization system. In order to improve traditional gradient optical flow, a pyramid multi-resolution coarse-to-fine search strategy was incorporated into this algorithm. Firstly, computing area affine transform parameters were selected as the final transform parameters. Then, in the compensation period, error control propagation method was selected to obtain long term stabilized sequence. The experiment results show the improved method can detect severe complex jitter, and can achieve the rotating precision less than 0.09°, translation precision less than 0.07, scaling precision less than 0.02, the compensation sequences＇ average PSNR raised 2.36 dB.