Since target information is easy to be lost or weaken in the current infrared and visible image fusion algorithms, a fusion algorithm based on non-subsampled contourlet transform and an improved pulse coupled neural network is proposed. First, the infrared and visible images which are preprocessed and registered are transformed through non-subsampled contourlet transform and the high-frequency coefficients and low-frequency coefficients of two images are obtained respectively. Then, the improved pulse coupled neural network is used to fuse the high-frequency coefficients of the images and the largest energy in a region is used to deal with the low-frequency coefficients. Finally, the fused coefficients are transformed by using NSCT inverse transform, so as to obtain the fused image. The experimental results show that the proposed algorithm can display more detail information of images in the subjective vision while its several objective data indicators are improved to a different extent.