Abstract: In order to solve the practical problem of the infrared small target’s detecting in the sky，an algorithm based on the wavelet transform and pipeline filter is proposed.Taking advantage of the excellent property of the transform，this algorithm analyzes the different property of the wavelet coefficients of noise，background edge and signal，then computes the normalized correlation coefficients between scale for the transform coefficients.According to the adaptive method of threshold，the coefficients of background edge and noise are suppressed and then the image which included the enhanced target is acquired by the inverse transform.Taking the target area into account，the reconstructed image is partitioned and the detecting result of single frame is obtained.Based on the continuity of target’s moving and the randomicity of noise，the detecting procedure is finished by the improved pipeline filter which sets the threshold of detection and position change respectively.Experimental results show that the method given by this paper can detect small target accurately.Compared with some traditional method，it has certain advantage in background suppressing and can acquire high SNR（signal noise ratio） value.

Key words: infrared small target, wavelet transform, correlation coefficient between scale, pipeline filter, background suppression, signal noise ratio

摘要： 针对空中远距离红外小目标检测的实际问题，提出了一种基于小波变换和管道滤波的检测算法。该方法利用小波变换的优良性质，通过分析噪声系数、背景边缘系数和目标系数在尺度间的不同特性，计算各个信号在尺度间的相关系数并归一化。按照自适应阈值法对噪声和背景边缘系数进行抑制，进而通过反变换得到抑制背景增强目标的图像。结合目标面积信息选择适当阈值，对重构图像进行分割生成单帧检测结果。基于目标运动的连续性和噪声的随机性，通过分别设置目标检测和位置变化门限，利用改进管道滤波完成小目标检测过程。试验结果表明，提出的算法能够准确地检测目标，相对于通常的小目标检测算法，该算法在背景抑制方面具有一定的优势，能够获得相对较高的信噪比。

关键词: 红外小目标, 小波变换, 尺度间相关系数, 管道滤波, 背景抑制, 信噪比