针对红外图像中多弹迹点检测精度不高的问题，对红外图像中弹迹点的特性进行了分析，提出了一种基于局部特性对比的多弹迹点检测算法用于有效检测红外图像中低信噪比条件下的多弹迹点。该方法利用同态滤波和中值滤波两种综合滤波方法减少光照不均的影响，提高图像信噪比。然后根据弹迹点在红外图像中自身的局部特性，采用局部特性对比并结合边缘检测精确检测弹迹点位置。从理论上分析了检测算法的有效性，并通过仿真实验与其他检测方法进行了对比。实验结果显示，本方法能够在低信噪比条件下有效检测出红外图像多弹迹点，与基于Top-hat 和基于局部均值等方法相比，检测准确度更高，鲁棒性更好。

Aiming at the problem that the precision of multi-shell track detection in an infrared image is not high, this study analyzed the characteristics of the shell track in an infrared image, and proposed a local-characteristics-contrast-based multi-shell track detection method, which was used to detect multi-shell tracks efficaciously in infrared images with low signal-to-noise ratios. The homomorphic filter and median filter were used jointly in the proposed method to reduce the influence of the uneven illumination and improve the signal-to-noise ratio. Then, according to the local characteristics of the infrared image, the local characteristics contrast and the edges were combined to detect the position of the shell track accurately. The efficacy of the proposed method was analyzed theoretically. Verification and contrast experiments were conducted. The experimental results show that the proposed method can detect the multi-shell track effectively in an infrared image with low signal-to-noise ratio. Compared with the top-hat detection methods and the local-mean detection methods, the proposed method is better in terms of detection precision and robustness.