In order to further improve the contrast and sharpness of the fuse d images,a method based on Rolling Guidance Filter and improved adaptive Unit- Linking Pulse Coupled Neural Network for infrared and visible images fusion is p r oposed in this paper.Firstly,the multi-scale decomposition of the source imag e s are carried out by RGF and Gaussian filter.Then,according to the maximum reg ional energy of the basic layer,a fusion rule combining the maximum regional en ergy with the source images is proposed.For detail layers,the corresponding ne uron ignition frequency map is obtained by using improved adaptive Unit-linking Pulse Coupled Neural Network,the edge features of ignition frequency map for ea ch pixel is calculated,and the larger coefficient of the two edge features is s elected as the fusion image coefficient.Finally,the fusion image is reconstruc ted by multi-scale.Experimental results show that the fusion algorithm in this paper can better highlight the target information of the images,provide rich ba ckground details,and achieve good fusion effects in terms of image clarity and visual effect of human eye.