中文摘要：

针对复杂红外背景中边缘噪声的干扰导致传统检测算法在低信噪比下目标检测概率较低的情况，提出了基于移动式加权管道滤波的弱小目标检测方法．该检测方法引入了自适应学习的思想，在利用管道滤波检测目标时，根据目标位置实时地修改加权的管道中心坐标位移，有效地抑制了边缘噪声对目标检测的干扰．与传统的管道检测方法相比，本方法能更好地抑制边缘噪声的影响，从而正确检测出真实目标．基于连续采集的红外序列图像进行的实验表明，当红外图像的信噪比大于等于1．5时，该方法均能有效地检测出弱小目标的轨迹．

英文摘要：

To deal with the lower detection probability in the low SNR by the traditional pipeline filter algorithm resulting from marginal noise interference in complicated IR background, a variable weighted pipeline filter algorithm is presented for detecting small targets in IR image sequences. The adaptive learning scheme is employed to modify the pipeline center position, i. e. , variable weighted pipeline center coordinates, according to targets＇s positions. This method can restrain effectively the interference caused by marginal noise. Compared with the traditional detection algorithm, this method is more suitable for dealing with failure detection and targets disappearing resulting from marginal pipeline noise. Experiments on long-rang IR image sequences show that the proposed algorithm can detect small targets within the IR image sequence efficiently with the SNR higher than 1.5.