A Survey of Multi-Focus Image Fusion Methods
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...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-06-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/12/12/6281 |
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| author | Youyong Zhou Lingjie Yu Chao Zhi Chuwen Huang Shuai Wang Mengqiu Zhu Zhenxia Ke Zhongyuan Gao Yuming Zhang Sida Fu |
| author_facet | Youyong Zhou Lingjie Yu Chao Zhi Chuwen Huang Shuai Wang Mengqiu Zhu Zhenxia Ke Zhongyuan Gao Yuming Zhang Sida Fu |
| author_sort | Youyong Zhou |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T00:27:48Z |
| format | Article |
| id | doaj.art-89218160be7246d7aedfcbb06c645ff8 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T00:27:48Z |
| publishDate | 2022-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-89218160be7246d7aedfcbb06c645ff82023-11-23T15:30:55ZengMDPI AGApplied Sciences2076-34172022-06-011212628110.3390/app12126281A Survey of Multi-Focus Image Fusion MethodsYouyong Zhou0Lingjie Yu1Chao Zhi2Chuwen Huang3Shuai Wang4Mengqiu Zhu5Zhenxia Ke6Zhongyuan Gao7Yuming Zhang8Sida Fu9School of Textile Science and Engineering, Xi’an Polytechnic University, Xi’an 710048, ChinaSchool of Textile Science and Engineering, Xi’an Polytechnic University, Xi’an 710048, ChinaSchool of Textile Science and Engineering, Xi’an Polytechnic University, Xi’an 710048, ChinaSchool of Textile Science and Engineering, Xi’an Polytechnic University, Xi’an 710048, ChinaSchool of Textile Science and Engineering, Xi’an Polytechnic University, Xi’an 710048, ChinaSchool of Textile Science and Engineering, Xi’an Polytechnic University, Xi’an 710048, ChinaSchool of Textile Science and Engineering, Xi’an Polytechnic University, Xi’an 710048, ChinaSchool of Textile Science and Engineering, Xi’an Polytechnic University, Xi’an 710048, ChinaSchool of Textile, Apparel & Art Design, Shaoxing University Yuanpei College, Shaoxing 312000, ChinaChina-Australia Institute for Advanced Materials and Manufacturing, Jiaxing University, Jiaxing 314001, ChinaAs 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.https://www.mdpi.com/2076-3417/12/12/6281image fusionmulti-focus imagefusion methodevaluation indicators |
| spellingShingle | Youyong Zhou Lingjie Yu Chao Zhi Chuwen Huang Shuai Wang Mengqiu Zhu Zhenxia Ke Zhongyuan Gao Yuming Zhang Sida Fu A Survey of Multi-Focus Image Fusion Methods Applied Sciences image fusion multi-focus image fusion method evaluation indicators |
| title | A Survey of Multi-Focus Image Fusion Methods |
| title_full | A Survey of Multi-Focus Image Fusion Methods |
| title_fullStr | A Survey of Multi-Focus Image Fusion Methods |
| title_full_unstemmed | A Survey of Multi-Focus Image Fusion Methods |
| title_short | A Survey of Multi-Focus Image Fusion Methods |
| title_sort | survey of multi focus image fusion methods |
| topic | image fusion multi-focus image fusion method evaluation indicators |
| url | https://www.mdpi.com/2076-3417/12/12/6281 |
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