An image fusion algorithm using region segmentation and contourlet transform is proposed. Firstly, region segmentation is done for source images, and ratio of region energy (RRE) and ratio of region sharpness (RRS) are presented to measure and extract region information. Then multiscale decomposition of the source images is carried out with the nonsubsampled contourlet transform. The high-frequency coefficients are fused with larger absolute value operator, and the low-frequency coefficients are fused with the region-based fusion rules and operators proposed. Finally the fused coefficients are reconstructed to obtain the fusion image. The fusion experiment for infrared and visible images is taken, and comparison between pixel-based à trous wavelet transform and contourlet transform is given. The results show that the fused image obtained by the presented algorithm can not only hold spectrum information of the visible image, but also inherit object information of the infrared image. The entropy of the fused image is about 10% greater than that of pixel-based fusion methods, and the cross entropy of the fused image is only 1% of that of pixel-based fusion methods.