In order to make full use of the important features of source images, an infrared and visible image fusion algorithm based on iterative guided filtering and multi-visual weight information is proposed. Firstly,input images are decomposed into base and detail layers by iterative guided filtering. Secondly,binary weight coefficients are synthetically determined by edge information,sharpness and contrast,which are then optimized by guided filtering to reduce noise and suppress artifacts. Finally,the fused image is reconstructed by the base layers and the detail layers on the basis of restructuring rules. Experiments show that compared with conventional multi-scale decomposition methods, the proposed method can better achieve separation of spatially-overlapped features, which can not only make the detail information more prominent,but also suppress the artifacts effectively.