红外图像小目标检测是精确制导武器的关键技术之一。将小波或Contourlet多尺度分析用于红外小目标检测具有一定的局限性。无下采样Contourlet变换（NSCT）是基于Contourlet变换的一种扩展，可以对图像进行灵活的多尺度、多方向和平移不变性分解。提出了一种基于NSCT的红外小目标检测算法。该算法首先对图像进行NSCT变换；然后利用能量法提取其局部纹理特征,并计算各点的特征向量与中心向量间的距离,得到一个相关的多尺度距离像；最后根据该距离像进行直方图统计,从而实现红外小目标的检测。与基于小波变换的红外小目标检测算法进行了比较。实验结果表明,该算法能较精确地检测出红外小目标，优于基于小波变换的方法。

The small target detection in infrared image is one of the crucial techniques for the precision guided weapon. Using wavelet and contourlet multi-scale analysis to detect small targets in infrared image has certain limitations. non-subsampled Contourlet transform (NSCT) is a new extension to contourlet transform. It is flexible multistage and shift invariant multidirectional. This paper presents a new small infrared target detection approach, which is based on nonsubsampled contourlet transform. This method picks up the texture characteristic from the maps after nonsubsampled contourlet transform, and calculates the distance between the characteristic vector and the center characteristic vector. This can gain a correlative multi-scale distance map. The histogram of distance map is employed for the automatic selection of threshold value. The experimental results are shown, and compared with the results based on wavelet transform in terms of detection precision and speed . The results show that the method of small infrared target detection based on nonsubsampled contourlet transform can precisely detect the small infrared target and it is better than the method based on wavelet transform.