The purpose of fusion of infrared and visible images is to generate more informative images for human observation or other computer vision tasks.In this paper,based on the great success of deep learning in the field of computer vision in recent years,an infrared and visible light image fusion algorithm based on convolutional neural network is proposed.Firstly,the input source image is decomposed at multiple scales by using a scale-aware edge protection filter composed of bootstrap filter and Gaussian filter.The base layer is fused by using the weighted average fusion rule of pixel intensity distribution,and the detail layer is extracted and fused by means of convolutional neural network.The experimental results show that the proposed algorithm can preserve the information of specific scales and reduce the influence of filtering on the edge details.After fusion,the image has less noise and the details present more naturally,which is suitable for human visual perception.