在红外图像预处理过程中，为有效保护图像的显著边缘信息，提出了一种融合全局梯度L0范数和局部显著性的保边平滑算法。首先，对红外图像进行拉普拉斯变换，采用嵌套矩形框快速估计边缘局部显著性，并利用均值与方差设计权重函数；其次，依据权重调节逼近项中每个像素的重要性，约束全局梯度的L0范数，建立模型；最后通过交替方向乘子法对模型求解，平滑红外图像，保护显著的边缘信息。实验结果表明，与其他保边平滑算法相比，所提算法能在平滑图像的同时，有效保护显著边缘，为进一步应用提供了理论支持。

In order to preserve the feature of salient edge for pre-processing of infrared images, an edge-preserving smoothing algorithm fused with L0 norm of global gradient and local saliency is proposed.First, Laplace transform is made to the infrared image, local edge saliency is estimated rapidly by the nested rectangles, and the weight function is designed by using mean and variance.Secondly, significance of each pixel in the approximation term is adjusted based on the weights, to restrain L0 norm of global gradient and build the optimization model.Finally, the model is solved by alternating direction method of multipliers, the infrared image is smoothed while preserving the local salient edges.Experimental result shows that:Comparing with other edge-preserving algorithms, our algorithm can smooth infrared images while preserve local salient edges effectively, which supplies a theoretical support for further application.