基于光流的红外目标被动测距技术

提出了一种应用在飞行器上的地面红外目标被动测距技术，该技术通过分析传感器的运动状态和目标在成像面上的光流来获得目标的距离信息。传统的被动测距算法直接用阈值分割提取运动目标，对于较大的红外目标，该方法误差较大。提出用光流参数聚类的方法获得运动目标。首先将中值滤波后的图像进行自适应阈值分割，得出含有目标的最小外接矩形，计算该矩形区域的光流场，从光流场聚类获得完整的目标区域。在已知目标象索在成像面上的位置和飞行器的运动状态的情况下，可以通过光流约束推导出每个象素的距离。最终的距离估计值是目标区域中所有象索距离的均值。该距离可以用来增强制导和改善弹道轨迹。实验结果表明，该方法适用于红外图像，且比传统方法获得的距离估计更准确。

A Method of Passive Ranging from Optical Flow of Infrared Target

A method using in aircraft of passive ranging from optical flow of infrared target is proposed. The range is achieved through analysis of the movement of the imaging sensor and the optical flow of the target. As the traditional passive ranging algorithm using the thresholding algorithm to achieve the target, the target is not integrated . We present the optical flow parameters clustering method to achieve the whole target. Firstly, we use median filter to remove the wildpoints and outliers of the image sequences. Secondly, the moving target is segmented by using auto- adaptive threshold algorithm. The whole target is obtained by the optical flow of the pixels inside the smallest rectangle that surrounds the target. A range expression at each pixel may directly calculate from pixel location and ownship motion. Finally, the range to the target is the average pixel ranges of the target area. The experiment result shows the algorithm can he applied to the infrared target passive ranging, which has better performance than traditional method.