基于LK和FAST的时间序列图像快速配准算法

LK光流算法是一种精确高效的特征跟踪算法，能够较大幅度提高图像配准的精度和速度。针对时间序列图像的配准问题，基于LK光流算法，通过基于图像金字塔的方式跟踪改进后的FAST特征角点，采用一种鲁棒的单应矩阵估计算法解算配准参数，提出了一种基于LK光流和改进FAST特征的实时鲁棒配准算法。通过一组时间序列图像从配准精度和配准速度两个方面对所提出算法的性能进行了验证分析，平均重投影误差为0.16，平均处理速度为30 Hz。实验结果表明，该算法能够提取稳定的FAST角点，快速准确地跟踪匹配序列图像之间的特征，较好地解决时间序列图像的实时配准问题。

Fast registration algorithm of image sequence by time based on LK and FAST

LK optical flow is an accurate and efficient feature tracking method which can be used to improve the performance of the image registration algorithm. For the registration problem of image sequence by time, a real-time and robust registration algorithm combining LK optical flow and improved FAST corners was proposed. The improved FAST corners was tracked by using the LK optical flow based on image pyramid and the registration parameters were calculated by adopting a robust homography estimation algorithm. In the experimental part, a real image sequence by time was used to verify the performance of the proposed algorithm from two aspects:registration accuracy and registration speed. The average re-projection error was 0.16 with the processing speed of 30 Hz. The experimental results show that the proposed algorithm can extract stable FAST corners and match the features between images efficiently and accurately, which solve the real-time registration problem of image sequence by time.