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%

The multifocus images fusion based on a generative gradient map

The limitation of camera lens is inability to make focus region for whole scene in one shot image. The camera creates one focus object for one image. It is needed several images to get many focus objects of the scene. It makes difficult to read many focus objects from several images. Multifocus image fusion is a process of combining many focus objects from several images into one image. This operation gives easier way to read focus information from many images clearer. It commonly needed in medical examination, robotics and bioinformatics fields. The clearness information enables machine, computer and human understand the image better and prevents any mistake. In an image, the clear object is only located in focus region. In order to generate all objects in focus region, the multi focus images will be fused into fused image. The methods generally use complicated mathematic equation and hard algorithm. In addition to handle the problem, we design a simple way and have accurate output. Our method is the multifocus image fusion based on generative gradient map. By generative gradient map, it quickly determines the initial prediction of focus region precisely. The Generative gradient map is the external information, generated from gradient of blurred random number image. This procedure substitutes complicated mathematical equations or hard algorithm sequence implementation. Finally, our algorithm able to produces a fused image with high quality. The assessment of our method is according to Mutual Information and Structure Similarity parameter