Multifocus image fusion algorithm using iterative segmentation based on edge information and adaptive threshold

This paper presents algorithm for multifocus image fusion in spatial domain based on iterative segmentation and edge information of the source images. The basic idea is to divide the images into smaller blocks, gather edge information for each block and then select the region with greater edge information to construct the resultant `all-in-focus´ fused image. To improve the fusion quality further, an iterative approach is proposed. Each iteration selects the regions in focus with the help of an adaptive threshold while leaving the remaining regions for analysis in the next iteration. A further enhancement in the technique is achieved by making the number of blocks and size of blocks adaptive in each iteration. The pixels which remain unselected till the last iteration are then selected from the source images by comparison of the edge activities in the corresponding segments of the source images. The performance of the method have been extensively tested on several pairs of multifocus images and compared quantitatively with existing methods. Experimental results show that the proposed method improves fusion quality by reducing loss of information by almost 50% and noise by more than 99%.