Abstract: Fusion of synthetic aperture radar (SAR) and multispectral (MS) images can contribute to a better visual perception of the objects observed. Unfortunately, many classical approaches have been proven to be unsuitable for this task due to their intrinsic differences in imaging mechanism, so a fusion algorithm based on non-subsampled contourlet transform(NSCT) and fuzzy c-means clustering(FCM) is proposed. The SAR image was segmented by FCM to extract the target area and background area ; the low-frequency sub-band and high-frequency directional sub-band were obtained by NSCT; for low-frequency part，different region was fused using different adaptive fusion criteria；for high-frequency part, regional block energy standard was used; finally, reconstructing images by NSCT inverse transform. Experimental results show that the fusion image can obtain target information of the SAR image and preserve spectral information of the multispectral image well. The proposed algorithm is better than most of the traditional fusion algorithms.