An infrared and visible image fusion algorithm based on Nonsubsampled Pyramid (NSP) and Latent Low Rank Representation (LatLRR) is proposed to address the problems of low image contrast and inconspicuous infrared features in the existing infrared and visible image fusion process.Firstly,the infrared and visible images are decomposed.The low frequency information of the source image is extracted by NSP decomposition,and the local structure information of the source image is extracted by LatLRR decomposition.Secondly,according to the characteristics of infrared low frequency information and visible low frequency information and the proportion of low frequency components in the fusion result image,the infrared pixel strength weight adjustment strategy is used to complete the fusion of low frequency information.At the same time,in order to maintain the balance of the local structure information of infrared and visible light during the fusion,the 1:1 fusion strategy based on the sum of pixel gray values is used.Finally,the idea of nonlinear transformation is introduced into image reconstruction to make the local structure information and low frequency information more perfectly fit.The experimental results show that the fusion result image can take into account the detail information in the visible image while greatly preserving the infrared features,and the algorithm can effectively fuse the infrared and visible images.