为了减少红外图像中起伏背景对弱小目标检测的影响，提出一种各向异性的红外背景预测方法。根据红外图像目标区域和平稳背景区域、起伏背景区域的局部梯度特性的差异，引入各向异性微分的思想，并将其边缘停止函数改进为方向梯度值的递增函数，然后用边缘停止函数最小两个方向值的均值作为背景预测值，实现了对不同方向特性背景区域的差异化预测。仿真实验表明，该算法选择性地保留了红外图像的平稳背景和起伏背景区域，达到了良好的背景预测效果。

For reducing the effect of undulate background in dim infrared targets detection, an anisotropic method is presented for infrared background prediction. According to differences of local gradient character among target region, smooth background region and undulate background region, the edge stopping function of anisotropic partial differential equations is improved to an increasing function with the value of the direction grads. Then the mean of the two least values of the edge stopping function is derived as the prediction value of the background. Simulation results show that the method selectively retains the smooth background region and the undulate background region, and achieves good prediction of background.