Aiming at the problems of edge blurring and detail loss in the fusion of infrared and visible image, this paper proposes a fusion algorithm based on alternating guided filter (AGF) and mask-guided convolutional neural network (CNN). Firstly, the source images is decomposed into a base layer and a detail layer by alternating guided filtering. Then, the base layer is passed through the fusion rule with energy attributes to get the base fusion image, and the detail layer is guided by the loss function based on the mask guidance to get the fused detail image by convolutional neural network. Finally, the base fusion image and the detail fusion image are summed to generate the final fused image. The experimental results demonstrate that the proposed method effectively retains abundant background edge texture information while highlighting significant thermal targets, and achieves better results in objective evaluation metrics compared with the comparison methods, which proves the superiority of the proposed algorithm.