The model based on fuzzy C-mean (FCM) clustering has the advantage of retaining most of the information of the original image for image segmentation. The adaptive dual-channel spiking cortical model (ADSCM) has the advantages of global coupling, pulse synchronization, less parameters, and high computational efficiency, and can process the information of darker images well. An infrared and visible light image fusion algorithm based on FCM and ADSCM is proposed. After the source image is decomposed by non-subsampled shearlet transform (NSST), the corresponding sub-band images are fused by combining FCM and ADSCM, and finally the new image is reconstructed by inverse NSST. Experimental results show that compared with other traditional methods, the proposed method can effectively extract the target information of the infrared image while retaining the visible light background information, and has obvious improvement in average gradient, mutual information, and edge retention factor.