A novel method based on region classification and multi-resolution transform was presented for the fusion of infrared and visual images to retain their spatial information and thermal target information and to improve their observability and intelligibility.The fusion process contained the following three steps.Firstly,infrared and visual images were fused by the Non-sampled Contourlet Transform(NSCT) to get lowpass subband coefficients and bandpass directional subband coefficients.Lowpass subband coefficients were fused by the region energy rule and the bandpass directional subband coefficients was fused based on the correlation rule of the bandpass directional subband coefficients.Then,the Structural Similarity Index(SSIM) between original images and intermediate fused image was computed.Based on the obtained SSIM,the images were classified in regions and the similarity region classification maps were obtained.Finally,to generate general and complementary regions,pixels of original images were classified by the threshold of similarity.In accordance with the concentrated similarity of different regions,the original images were fused for the second time and the final fused images were obtained.In this method,the general and complementary regions of infrared and visual images were distinguished effectively.The experimental results show that the method is better in fusing infrared and visual images than some current methods,such as NCST,Dual-tree Complex Wavelet Transform(DTCWT),Redundant Discrete Wavelet Transform(RDWT),and Discrete Wavelet Transform(DWT).As compared with the NSCT method in two group images,their quality indexes have been increased by 16%,85%,54%,36% and 18%,102%,84%,41%,respectively.