Changchun Institute of Optics,Fine Mechanics and Physics,CAS
Multi-Exposure Image Fusion Techniques: A Comprehensive Review | |
F. Xu; J. H. Liu; Y. M. Song; H. Sun and X. Wang | |
2022 | |
发表期刊 | Remote Sensing
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卷号 | 14期号:3页码:31 |
摘要 | Multi-exposure image fusion (MEF) is emerging as a research hotspot in the fields of image processing and computer vision, which can integrate images with multiple exposure levels into a full exposure image of high quality. It is an economical and effective way to improve the dynamic range of the imaging system and has broad application prospects. In recent years, with the further development of image representation theories such as multi-scale analysis and deep learning, significant progress has been achieved in this field. This paper comprehensively investigates the current research status of MEF methods. The relevant theories and key technologies for constructing MEF models are analyzed and categorized. The representative MEF methods in each category are introduced and summarized. Then, based on the multi-exposure image sequences in static and dynamic scenes, we present a comparative study for 18 representative MEF approaches using nine commonly used objective fusion metrics. Finally, the key issues of current MEF research are discussed, and a development trend for future research is put forward. |
DOI | 10.3390/rs14030771 |
URL | 查看原文 |
收录类别 | sci ; ei |
语种 | 英语 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ciomp.ac.cn/handle/181722/66868 |
专题 | 中国科学院长春光学精密机械与物理研究所 |
推荐引用方式 GB/T 7714 | F. Xu,J. H. Liu,Y. M. Song,et al. Multi-Exposure Image Fusion Techniques: A Comprehensive Review[J]. Remote Sensing,2022,14(3):31. |
APA | F. Xu,J. H. Liu,Y. M. Song,&H. Sun and X. Wang.(2022).Multi-Exposure Image Fusion Techniques: A Comprehensive Review.Remote Sensing,14(3),31. |
MLA | F. Xu,et al."Multi-Exposure Image Fusion Techniques: A Comprehensive Review".Remote Sensing 14.3(2022):31. |
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Multi-Exposure Image(3836KB) | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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