Multimodal Image Fusion Method Based on Multiscale Image Matting

Multimodal image fusion combines the complementary information of multimodality images into a single image that preserves the information of all the source images. This paper proposes a multimodal image fusion method situated on image enhancement, edge detection, multiscale sliding window, and image matting to obtain the detailed region information of the input images. In the proposed system, firstly the multimodality input images are rectified via a contrast enhancement method through which the intensity distribution is refined for clear vision. The spatial gradient edge detection method is utilized for separating the edge information from the contrast-enhanced images. These edges are then used by a multiscale sliding window method to provide global and local activity level maps. These activity maps further generate trimap and decision maps. Finally, by employing the improved decision maps and fusion rule the fused image is acquired.