Novel Image Fusion Algorithms Based On Intuitionistic Fuzzy Sets

Aim to improve the defect and disadvantage of image processing based on classical fuzzy sets theory, in this paper, we study the key question and difficult point of image fusion algorithms based on intuitionistic fuzzy sets theory.Via the intensive study of intuitionistic fuzzy set, combine the characteristic of the image, we compute two important parameters:the intuitionistic index and the intuitionistic fuzzy similarity. As well, we present one new image fusion algorithm in spatial domain and another two new image fusion algorithms with non-subsampled contourlet transform, the two algorithms are based on intuitionistic index and intuitionistic similarity, respectively.In addition, We do experiments of all the algorithms above on MATLAB, fuse the multi-focus images and remote sensing images. Moreover, we also use several classical image fusion algorithms on the images, we also use several image evaluation criteria to evaluate the images. We compare these new algorithms to some classical image fusion algorithms. The results show, for multi-focus image, these new algorithms are better comparing to other algorithms, and they can get a good fusion result, especially the non-subsampled contourlet transformation algorithm using the intuitionistic index. For remote sensing image, these new algorithms are not the best, but they can also get a well fusion result. How to optimize the algorithm for making better result on remote sensing image, could be the next research subject in the future.