Aiming at the characteristics of the infrared and visual image,an algorithm for image fusion based on Non-Subsampled Contourlet Transform (NSCT) and hybrid particle swarm optimization is proposed.NSCT is used for decomposition of the infrared and visual source images.To the low-frequency sub-images,an improved weighted average method based on regional averages is adopted for neighborhood fusion.To the top layer of the high-frequency sub-images,the fusion method of “choosing the biggest” for the regional standard deviation is adopted;to the other layers of the high-frequency sub-images,the hybrid particle swarm optimization is used for selecting the threshold value,and the neighborhood algorithm based on the average gradient selection is adopted for fusion.Finally,NSCT inverse transform is utilized to obtain the fused image.The experimental results show that the method can obtain the ideal fusion image and more detail information.