A Survey of Multi-Focus Image Fusion Methods
Youyong Zhou, Lingjie Yu, Chao Zhi, Chuwen Huang, Shuai Wang, Mengqiu Zhu, Zhenxia Ke, Zhongyuan Gao, Yuming Zhang, Sida Fu
Abstract
As an important branch in the field of image fusion, the multi-focus image fusion technique can effectively solve the problem of optical lens depth of field, making two or more partially focused images fuse into a fully focused image. In this paper, the methods based on boundary segmentation was put forward as a group of image fusion method. Thus, a novel classification method of image fusion algorithms is proposed: transform domain methods, boundary segmentation methods, deep learning methods, and combination fusion methods. In addition, the subjective and objective evaluation standards are listed, and eight common objective evaluation indicators are described in detail. On the basis of lots of literature, this paper compares and summarizes various representative methods. At the end of this paper, some main limitations in current research are discussed, and the future development of multi-focus image fusion is prospected.