Region-based Image Fusion by Using Region Priorities

In this paper, a new region-based approach to multi-resolution image fusion is presented. To make fusion decision better, a master image is selected from the source images. Then, it is segmented using the background subtraction based Mumford and Shah algorithm, which significantly improves the segmentation at quality and convergence speed. After that, the fusion rules on every region of the image are determined based on the best priority-first strategy. Moreover, the fusion on the whole image domain is replaced by using different rules on every segmented region of the image. The corresponding regions in other images are located by linear mapping methods. Some numerical results have been given and compared to the pixel-based fusion methods. Despite an increase in complexity, more intelligent fusion rules may be applied to remove side effects like reducing contrast and sensitive to error of registration.