Feature-based Exposure Fusion
Feature-Based Exposure Fusion is a computational imaging technique in high-dynamic-range imaging that combines multiple differently exposed images by leveraging distinctive visual features—such as edges, textures, and salient structures—to guide the fusion process, thereby preserving optimal exposure in salient regions while enhancing overall image quality.
7
Publications
204
Citations
22
Authors
13
Institutions
Publications per year
2017–2026
5
Parents
7
Holistic Dynamic Frequency Transformer for image fusion and exposure correction
Xiaoke Shang, Gehui Li, Zhiying Jiang et al. · Information Fusion · 2023 · 32 citations
Arts, Radiology, Diagnostic Imaging +15
1–5 of 7
22
1
h-index
1
h-index
1
h-index
1
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1
h-index
1–5 of 22
13
Dalian University of Technology
Dalian, China
2 h-index
5 publications
166 citations
Suzhou University of Science and Technology
Suzhou, China
1 h-index
1 publications
35 citations
Shandong University of Finance and Economics
Jinan, China
1 h-index
1 publications
17 citations
Jinling Institute of Technology
Jiangning, China
1 h-index
1 publications
17 citations

Huazhong University of Science and Technology
Wuhan, China
1 h-index
1 publications
35 citations
Nanyang Technological University
Singapore, Singapore
1 h-index
1 publications
18 citations
Weifang University
Weifang, China
1 h-index
1 publications
17 citations

University of Toronto
Toronto, Canada
1 h-index
2 publications
70 citations
1–8 of 13
2 publications · 35 citations
2
h-index
1 publications · 41 citations
1
h-index
1 publications · 32 citations
1
h-index
1 publications · 18 citations
1
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1 publications · 43 citations
1
h-index
1–5