Fuzzy image fusion algorithm based on SGNN

The optimized order and number for current M-L optimization algorithms are presented; and the composite processing method of clipping first and optimizing again for the generated SGNN network is proposed. Then, after clustering the original image element, the proposed composite processing method is added to get better element clustering. Finally, aiming at the large grayscale differences of every class's center and the different class number because of the different grayscale characteristics of images acquired from different sensors, a modified fusion method is proposed. Simulation result verifies the superiority of the proposed fuzzy fusion algorithm.