高动态条件下增量惯导信息辅助的空地红外弱小移动目标检测算法（特邀）

红外弱小移动目标检测技术是计算机视觉的研究热点和难点。针对机载高动态条件下的空地目标检测存在的场景变化动态、背景干扰强度大、目标运动规律未知等挑战，提出了一种新型的基于增量惯导信息辅助的空地红外弱小移动目标检测算法。为了解决传统惯导信息预测的漂移误差问题，提出了增量惯导信息概念，设计了增量惯导信息的位置预测模型，实现了对目标点的准确预测。构建了基于增量惯导信息辅助与背景差分的移动目标检测框架，通过增量惯导信息对不同位姿下的成像进行校正，引入基于爬山法互相关匹配算法计算校正后图像的平移参数，采用高斯加权对背景图像进行估计，最后通过图像分割检测弱小移动目标。仿真实验验证了文中设计检测算法的有效性和精确性。

Infrared dim moving target detection algorithm assisted by incremental inertial navigation information in highdynamic air to ground background (Invited)

Infrared dim moving target detection technology is a hot and difficult research area in computer vision. To deal with the challenges of target detection with airborne in high dynamic air to ground background, such as dynamic scene change, large background interference intensity and unknown target motion law, a novel incremental inertial navigation information assisted air to ground infrared dim moving target detection algorithm was proposed. To solve the drift error problem of traditional inertial navigation information prediction, the concept of incremental inertial navigation information was put forward. The location prediction model of incremental inertial navigation information (LPI) was designed and the accurate prediction of the target point was achieved. A moving target detection framework was constructed based on inertial navigation information assistance and background difference, which corrected the images under different positions and attitudes by LPI. The cross correlation matching algorithm based on mountain climbing method was introduced to calculate the translation parameters, and Gaussian weighting was used to estimate the background. The dim moving target could be detected by adaptive threshold segmentation. The simulation experiments verified the effectiveness and accuracy of the proposed detection algorithm.