Region-based Image Fusion
Region-Based Image Fusion is a type of image fusion method that operates by partitioning source images into distinct regions based on spatial or feature-domain homogeneity and then combining them through region-level analysis to preserve structurally significant information in the fused output.
161
Publications
13K
Citations
471
Authors
169
Institutions
Publications per year
2017–2026
52
Parents
161
A new look at IHS-like image fusion methods
Te‐Ming Tu, Shun-Chi Su, Hsuen-Chyun Shyu et al. · Information Fusion · 2001 · 902 citations
Pixel- and region-based image fusion with complex wavelets
J. Lewis, R.J. O'Callaghan, S.G. Nikolov et al. · Information Fusion · 2005 · 829 citations
Deep learning for pixel-level image fusion: Recent advances and future prospects
Yü Liu, Xun Chen, Zengfu Wang et al. · Information Fusion · 2017 · 725 citations
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169

University of Bristol
Bristol, United Kingdom
9 h-index
28 publications
6.3K citations

Beihang University
Beijing, China
8 h-index
22 publications
730 citations
Yunnan University
Kunming, China
4 h-index
18 publications
531 citations

Hunan University
Changsha, China
4 h-index
12 publications
1.1K citations

Shanghai Jiao Tong University
Shanghai, China
4 h-index
10 publications
242 citations

Xidian University
Xi'an, China
4 h-index
12 publications
484 citations

Chongqing University
Chongqing, China
3 h-index
7 publications
576 citations
Jilin University
Changchun, China
3 h-index
7 publications
155 citations
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17 publications · 5.7K citations
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5 publications · 151 citations
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4 publications · 160 citations
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3 publications · 186 citations
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ARCME · 3 publications · 422 citations
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