针对天空背景下云层对弱小目标的干扰，以及靶场实验中观测设备所产生的拖影现象对目标检测所带来的干扰等问题,提出了一种基于局部行像素对比度的空中红外弱小目标检测算法，用于检测低信噪比条件下的空中红外弱小目标。该方法利用中值滤波和形态滤波获取滤波图像，结合目标区域像素特点提取滤波图像中感兴趣区域，然后利用局部行像素对比度的方法检测目标位置，极大提高了检测效率，缩短了检测时间。从理论上介绍和分析了该算法对红外弱小目标图像检测算法的有效性，并通过Matlab仿真实验与其他检测算法进行了对比。实验结果表明，所提算法能够在低信噪比条件下更加有效地检测出空中红外弱小目标，检测精度更高、效果更好。

In view of the interference of ghosting phenomenon to target detection, which is caused by the observation equipment in range experiment, and the interference of clouds to dim small target in the sky background, an algorithm for aerial infrared small target detection is proposed based on partial row pixel contrast. The algorithm can be used for detecting aerial infrared dim targets under low SNR condition. The method uses median filter and morphological filtering to obtain filtered image, extracts the region of interest from the filtered image based on the pixel feature of the target area;then uses the partial row pixel contrast to detect the position of the target. The method can greatly improve the detection efficiency with less time. This paper introduces and analyzes the theoretical effectiveness of the infrared small target image detection algorithm, and makes comparison of it with other algorithms through the Matlab simulation. The experimental results show that the proposed algorithm can detect the aerial infrared dim small targets more effectively under the condition of low SNR with higher accuracy and better performance.