针对存在复杂背景干扰和噪声的红外图像弱小目标检测问题，提出了一种非下采样Contourlet变换(NSCT)的改进的红外弱小目标检测方法。首先对含弱小目标的红外图像进行预处理，然后利用NSCT进行变换，并利用改进的非线性映射函数和能量交叉融合相结合的方法实现了背景杂波的抑制，最后引入Otsu算法进行阈值分割分离出红外弱小目标。通过与同类弱小目标检测算法的对比实验，验证了该方法的有效性。

For the problem of small infrared target detection with complex background interference and noises, an improved dim small infrared target detection algorithm based on nonsubsampled Contourlet transform (NSCT) is put forward. Firstly, the infrared image with dim small target is preprocessed. Then, the NSCT is implemented, by combining the improved nonlinear map function and energy cross fusion to suppress the background clutters. Finally, threshold segmentation using the Otsu algorithm is used to isolate the dim small infrared target. Compared with the similar small target detection algorithm, the method can effectively detect the small infrared target.