Model-based Bayesian Fusion-Net for infrared and visible image fusion Article Swipe
Xiaotian Li
,
Kuang Yafang
,
Cai Ziyi
,
Ning Chu
,
Ali Mohammad‐Djafari
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1186/s13640-025-00680-5
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1186/s13640-025-00680-5
Infrared and visible image fusion aims to generate fused images that maintain the advantages of each source such as temperature information and detailed textures. This paper presents Bayesian Model-based Fusion-Net, a novel approach for infrared and visible image fusion. By formulating image fusion as an inverse problem within a hierarchical Bayesian framework, our method leverages physical priors and data-driven techniques to enhance model interpretability and transferability. Compared to traditional and deep learning-based fusion methods, the proposed Bayesian Model-based Fusion-Net achieves promising performance with significantly reduced computational complexity (0.07G FLOPs). Extensive experiments on multiple datasets, including industrial public dataset, demonstrate the effectiveness of the proposed method in preserving texture details, maintaining structural integrity, and enhancing feature clarity. Furthermore, our approach exhibits robustness when trained with limited data, maintaining consistent performance even when using only 10% of the training dataset. These characteristics make the proposed Bayesian Fusion-Net particularly suitable for industrial monitoring applications where computational resources and the amount of training dataset are limited.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1186/s13640-025-00680-5
- https://jivp-eurasipjournals.springeropen.com/counter/pdf/10.1186/s13640-025-00680-5
- OA Status
- gold
- References
- 49
- Related Works
- 10
- OpenAlex ID
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4413023824Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1186/s13640-025-00680-5Digital Object Identifier
- Title
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Model-based Bayesian Fusion-Net for infrared and visible image fusionWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-08-06Full publication date if available
- Authors
-
Xiaotian Li, Kuang Yafang, Cai Ziyi, Ning Chu, Ali Mohammad‐DjafariList of authors in order
- Landing page
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https://doi.org/10.1186/s13640-025-00680-5Publisher landing page
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https://jivp-eurasipjournals.springeropen.com/counter/pdf/10.1186/s13640-025-00680-5Direct link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://jivp-eurasipjournals.springeropen.com/counter/pdf/10.1186/s13640-025-00680-5Direct OA link when available
- Concepts
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Artificial intelligence, Image fusion, Fusion, Bayesian probability, Biometrics, Infrared, Pattern recognition (psychology), Computer science, Net (polyhedron), Computer vision, Image (mathematics), Mathematics, Physics, Optics, Linguistics, Geometry, PhilosophyTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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49Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| primary_location.license | cc-by-nc-nd |
| primary_location.pdf_url | https://jivp-eurasipjournals.springeropen.com/counter/pdf/10.1186/s13640-025-00680-5 |
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| primary_location.raw_source_name | EURASIP Journal on Image and Video Processing |
| primary_location.landing_page_url | https://doi.org/10.1186/s13640-025-00680-5 |
| publication_date | 2025-08-06 |
| publication_year | 2025 |
| referenced_works | https://openalex.org/W2914139557, https://openalex.org/W2809795042, https://openalex.org/W2744019306, https://openalex.org/W2901978237, https://openalex.org/W2049266046, https://openalex.org/W2019873321, https://openalex.org/W2112275169, https://openalex.org/W2600975391, https://openalex.org/W2417728490, https://openalex.org/W2097259623, https://openalex.org/W2306859282, https://openalex.org/W2182332322, https://openalex.org/W2744070429, https://openalex.org/W1965739998, https://openalex.org/W2102470101, https://openalex.org/W2003026516, https://openalex.org/W1998279052, https://openalex.org/W2589745805, https://openalex.org/W3111354027, https://openalex.org/W2023497873, https://openalex.org/W2610070095, https://openalex.org/W4362014679, https://openalex.org/W3168997536, https://openalex.org/W2998674422, https://openalex.org/W2999838674, https://openalex.org/W3107998196, https://openalex.org/W2921353139, https://openalex.org/W2912147220, https://openalex.org/W4312052673, https://openalex.org/W3011768656, https://openalex.org/W2909431601, https://openalex.org/W2798987894, https://openalex.org/W3198582484, https://openalex.org/W3035467948, https://openalex.org/W4293704605, https://openalex.org/W2078855750, https://openalex.org/W4289996737, https://openalex.org/W2402829325, https://openalex.org/W2275363859, https://openalex.org/W4205852334, https://openalex.org/W2998785217, https://openalex.org/W4312725970, https://openalex.org/W2777029899, https://openalex.org/W4386076504, https://openalex.org/W3105639468, https://openalex.org/W4309196273, https://openalex.org/W3104771364, https://openalex.org/W4281898289, https://openalex.org/W4404464843 |
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