Image fusion is the process of integrating useful or complementary information from multiple images into one a single image.In this paper,an infrared and visible image fusion algorithm based on guided filter multi scale decomposition is proposed.Based on the traditional guided filter image fusion algorithm,a dual guided filter is utilized to replace the mean filter to decompose the source image into small scale texture details,large scale edges and basic images.The texture details and edge layer images are directly used to construct saliency maps,which can be instead of additional feature extraction operations to highlight the saliency information of the source image while greatly reducing the complexity of the algorithm.Using saliency map and sigmoid function to construct weight map,the visually meaningful information in the source image is injected into the fusion image.The color information of images can be better preserved by using the color model transformation and fusion method.Qualitative and quantitative experimental results show that the fusion effect of the proposed algorithm is further improved compared with the traditional guided filtering image fusion algorithm.