Multi-exposure Image Fusion
Multi-Exposure Image Fusion is a computational imaging technique that combines multiple images of the same scene captured at different exposure levels into a single image, preserving well-exposed details across all regions by leveraging complementary information from each exposure.
160
Publications
12.4K
Citations
454
Authors
181
Institutions
Publications per year
2017–2026
109
Parents
160
Hao Zhang, Han Xu, Yang Xiao et al. · Proceedings of the AAAI Conference on Artificial Intelligence · 2020 · 570 citations · Full text
Tom Mertens, Jan Kautz, Frank Van Reeth · 2007 · 470 citations
Robust Multi-Exposure Image Fusion: A Structural Patch Decomposition Approach
Kede Ma, Hui Li, Hongwei Yong et al. · IEEE Transactions on Image Processing · 2017 · 353 citations
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181

University of Waterloo
Waterloo, Canada
9 h-index
19 publications
2.5K citations
Institute for Infocomm Research
Singapore, Singapore
8 h-index
12 publications
1K citations
Wuhan University
Wuhan, China
7 h-index
12 publications
2.6K citations
Nanyang Technological University
Singapore, Singapore
6 h-index
11 publications
1.2K citations
Tokyo Metropolitan University
Tokyo, Japan
5 h-index
13 publications
350 citations

Chinese Academy of Sciences
Beijing, China
5 h-index
15 publications
493 citations

City University of Hong Kong
Hong Kong, Hong Kong
5 h-index
5 publications
520 citations
University of Science and Technology of China
Hefei, China
5 h-index
16 publications
680 citations
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23 publications · 3.6K citations
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8 publications · 601 citations
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6 publications · 412 citations
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6 publications · 485 citations
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Conference · 4 publications · 980 citations
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