A Novel Fusion Approach of Multi-exposure Image

A method based on genetic algorithms (GA) for fusing multiple images of a static scene into an image with maximum information content is introduced. It partitions the image domain into uniform blocks and for each block selects the image that contains the most information within that block. The selected images are then blended together using rational Gaussian blending functions that are centered at the blocks. In this paper, we employ GA for optimizing both the block size and width of the blending functions. We also examine the effectiveness of our scheme by checking the fitness function in GA, which includes both factors related to information and human vision.