为检测强云杂波背景中的红外弱小运动目标，结合反锐化掩模理论，提出了一种基于曲线波变换的多尺度反锐化掩模红外图像云层背景抑制新方法。首先，根据红外目标和背景杂波的特性，采用二代曲线波变换对图像进行多尺度、多方向分解，提取图像的多尺度和方向细节特征，然后，根据目标和背景杂波子带系数的差异，通过应用反锐化掩模理论调整分解后的各子带系数，从而将红外图像中弱小目标信号和背景杂波分离，达到抑制背景的目的。实验结果显示，与最大中值(ＭＭｅｄ)和二维最小均方误差(ＴＤＬＭＳ)方法比较，该方法对信杂比较低的红外弱小目标复杂云层背景从主观视觉和数值指标都具有良好抑制效果。

To detect a dim and small infrared moving target under heavy clouds cluttered background, the infrared image background clouds suppression method based on curvelet transform is proposed. According to characterization of infrared target and background clutter, firstly, the second curvelet transform is adopted to decompose the input infrared image into different scales and directions, from which multiscale and directional detail features of the image are extracted. Then, according to difference between target and background clutter coefficients of subbands, and unsharped masking method is introduced to suppress background details and enhance target information for separation cluttered background with dim and small target signal. Compared with max median (MMed) and twodimensional least means square (TDLMS) methods, experimental results demonstrate that the proposed method can suppress complicated background in dim and small target image effectively, both in subject inspection and value index.