Aiming at the insufficient preservation of color and details existed in traditional multi-exposure image fusion, a novel multi-exposure image fusion algorithm based on adaptive segmentation was proposed. Firstly, the input image was divided into blocks with the same color by super-pixel segmentation. Then structural decomposition was conducted on the image blocks to obtain three individual components. Different fusion rules were designed according to the characteristics of each component, so as to preserve the color and details in original images. Then, the weight map of each component, signal strength component and brightness component were smoothed by guided filtering, effectively overcoming the problem of block effect, retaining the edge information in the source image and reducing the artifacts. Finally, the fusion image was obtained by reconstructing three fused components. The experimental results show that, compared to the traditional fusion algorithms, the proposed algorithm has the average increase of 53.6% in Mutual Information (MI) and 24.0% in Standard Deviation (SD) respectively. The proposed image fusion algorithm can effectively preserve the color and texture details of input images.