面向经纬仪图像序列的关键帧提取算法

将传统的关键帧提取算法应用于经纬仪图像序列时，关键帧序列中会包含大量的非稳定跟踪图像帧。为了在关键帧提取过程中更好地保留目标稳定跟踪测量信息，该文在分析了经纬仪图像序列的特点后，构建了一种基于局部极大值的经纬仪图像序列关键帧提取算法。该算法首先计算图像序列的帧间差分，然后使用汉宁窗函数对帧间差分进行平滑，最后基于平滑后的帧间差分局部极大值来提取关键帧。实验结果表明:提出的算法相对于传统的帧间差分强度排序方法能更好地保留目标的跟踪测量信息，提取的关键帧在整个跟踪测量图像序列中分布更为均匀，包含的场景信息更为丰富。

Key frame extraction algorithm for theodolite image sequence

When the traditional key frame extraction algorithm is applied to the theodolite image sequence, a large number of unstable tracking image frames will be extracted. In order to better retain the stable tracking measurement information of the target, after analyzing the characteristics of the theodolite image sequence, a key frame extraction algorithm for the theodolite image sequence based on the local maximum was constructed. Firstly, the frame difference of the image sequence was calculated by the algorithm. Then, the Hanning window function was used to smooth the frame difference. Finally, based on the smoothed local maximum of frame difference, the key frame was extracted. The experimental results show that the proposed algorithm can better retain the tracking measurement information of the target compared with the traditional frame difference intensity sorting method. The extracted key frames are more uniformly distributed in the entire tracking measurement image sequence, and the scene information contained is more abundant.