Due to the poor visibility of visible images in low-light environment, an image fusion algorithm based on contrast enhancement and cauchy fuzzy function is proposed to improve the fusion effect of infrared and low-light-level visible images. Firstly, the visibility of dark region of low-light-level visible image is improved by the adaptive enhancement of improved guided filtering. Secondly, non-subsampled shearlet transform is used to decompose infrared and enhanced low-light-level visible images to obtain corresponding low-frequency and high-frequency components. Then, the intuitive fuzzy sets were used to construct the cauchy membership function and adaptive dual - channel spiking cortical model to fuse the low-frequency and high-frequency components. Finally, the fusion image are reconstructed by using non-subsampled shearlet inverse transform. Experimental results show that compared with other fusion algorithms, the algorithm can effectively enhance the dark area of the low-light-level visible image and retain more background information, thus improving the contrast and clarity of the fusion image.