摘要
提出一种基于梯度优化的不同运动幅度视频图像光流估计的新算法。先用Loggabor滤波器对原视频图像进行相位、尺度滤波,再用所得的特征图像来计算时空梯度,最后根据时空梯度计算光流。该算法模型同时运用由粗到精的图像金字塔方法对视频图像分层处理。理论分析和实验结果表明,该算法适用于大幅度的视频运动光流估计,不仅能得到适合人眼视觉分辨率特性的图像,而且使时空梯度更加优化,光流计算更准确。并且在时间复杂度上与传统光流计算方法相当,在计算精度上优于Horn和Schunck、段先华等人提出的算法。
A new algorithm based on gradient optimization is proposed for optical flow estimation of video images with different motion ranges.The original video images are transformed by using Loggabor filtering on phases and measures,and then the spatio-temporal gradient is calculated by using the obtained feature images.The optical flow is calculated with the spatio-temporal gradient.The video images are layered and processed with coarse-to-fine image pyramid method.The theoretical analysis and experimental results show that the algorithm is suitable for the video optical flow motion estimation of the significant range.It can not only obtain the video images following the human visual resolution characteristics,but also optimize the spatio-temporal gradient,while the optical flow calculation is more accurate.Besides,the time complexity of this algorithm is equivalent to that of the traditional optical flow method,and the accuracy of the algorithm is superior to the methods suggested by Horn-Schunck,Duan,et al.
出处
《重庆大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2011年第12期121-125,共5页
Journal of Chongqing University
基金
国家自然科学基金资助项目(11071226)
重庆市教委科研基金资助项目(KJ100505)
