Multi-Focus Image Fusion Algorithm using Phase Congruency and K-Means Clustering

In this paper, a novel image fusion algorithm based on phase congruency is presented. The proposed algorithm has two steps. In the first step, the information content of the input images is evaluated by using phase congruency model. In this step, the main idea of the work is based on the fact that image features like edges are located in the points of image which frequency components have the maximum phase congruency. In the second step, the dominant features are selected and accordingly image fusion is done. Also, for reducing the computational complexity and improving the overall performance, the proper blocks are chosen by determining the appropriate threshold and the other blocks are chosen using K-means clustering algorithm through an iterative process. The experimental results on several images show that the proposed method has significant advantages compared to the other existing methods.