Fusion method of dual color mid-wave infrared images is presented in this paper in order to solve such frequently rising issues as limited contrast ratio improvement and serious marginal area distortion in the fusion of the above two images using multi-scale top-hat decomposition. The detailed procedure is shown as the following: A low-frequency component image and a sequence of support value images of the two subdivision band images of mid-wave infrared are obtained respectively with support value transform. Multi-scale bright and dim information are first extracted from the last layer of low-frequency image using the multi-scale top-hat decomposition method respectively. Then they are fused by selecting the maximum gray of each pixel in two subdivision band images of mid-wave infrared respectively. Following that, the two resulted images are enhanced using the gray-scale normalization and Gaussian filtering and fused with the two low-frequency images to get the low-frequency fusion image. After that, this fusion image is reversely transformed with the support sequence image fused by selecting the maximum gray. The final image is got at last. The result shows that compared with the simple support value transform fusion and the multi-scale top-hat decomposition fusion, the method suggested in this paper successfully increases the contrast ratio by 11.69%, decreases the distortion factor by 63.42%, and increases the local coarseness by 38.12%. All these show that the validity of fusion method proposed has been proved, which indicates that both bright and dim information from low-frequency images can effectively solve the contradiction between improving fused image’s contrast ratio and reducing its’ distortion after the both are fused and enhanced respectively, and then fused with the two low-frequency images, which provides a new useful method for improving the quality of fused inferred images.