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

Authors

454

  1. ZW
    Zhou Wang

    University of Waterloo, Canada

    8 publications · 1K citations

    8

    h-index

  2. ZL
    Zhengguo Li

    Institute for Infocomm Research, Singapore

    8 publications · 645 citations

    8

    h-index

  3. KM
    Kede Ma

    University of Waterloo, Canada

    7 publications · 1.1K citations

    7

    h-index

  4. JM
    Jiayi Ma

    Wuhan University, China

    6 publications · 1K citations

    6

    h-index

  5. HL
    Hui Li

    Hong Kong Polytechnic University, Hong Kong SAR China

    5 publications · 710 citations

    5

    h-index

1–5 of 454

Venues

  1. IEEE Transactions on Image Processing

    23 publications · 3.6K citations

    23

    h-index

  2. Information Fusion

    8 publications · 601 citations

    8

    h-index

  3. IEEE Transactions on Consumer Electronics

    6 publications · 412 citations

    6

    h-index

  4. 6

    h-index

  5. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 4 publications · 980 citations

    4

    h-index

1–5