Aimed at the infrared and visible light images in the same scene,a fusion algorithm based on region segmentation and nonsubsampled contourlet transform (NSCT）is proposed in this paper.Firstly,regional segmentation and regional association are used in the infrared and visible light images,the joint region map is divided into the target area,the background area and gray area.Then,the source images are performed to multi-scale and multi-direction decomposition in NSCT domain,after which both low-pass sub band coefficients and band-pass directional sub band coefficients are divided into three areas in accordance with the joint region map.According to the characters of the different areas,different fusion rules are designed in NSCT domain.Finally,the fused result is obtained through inverse NSCT.The propose algorithm has been experimented on three different scene images,experimental results are compared both in subjective and objective standards.It is showed that the algorithm can not only keeps the spectrum information of visible light image completely and richly,but also extracts the target characters of infrared ray image accurately and effectively.The proposed algorithm is superior to those conventional fusion methods based on nonsubsampled contourlet transform,using pixel or neighborhood energy,and is feasible and effective,also can manifest better fusion effect.