Journal of System Simulation
Abstract
Abstract: In order to solve the problem that existing infrared and visible light image fusion techniques often suffer from artifacts caused by insufficient contrast, spectral distortion, and high computational complexity, a fusion framework based on ResNet-50 and Laplacian filtering was proposed. ResNet-50 was used to extract shallow and deep features, followed by multi-scale feature fusion. Laplacian filtering was applied to optimize feature information, and an automatic discriminator was introduced to further improve the fusion effect. Simulation results show that, compared with comparison algorithms, the proposed method achieves an average increase of 2.71% and 2.16% in information entropy, 5.98% and 7.86% in visual information fidelity, and 12.57% and 14.63% in wavelet-based feature mutual information on the TNO and VIFB datasets, respectively, which proves its effectiveness in improving image fusion quality.
Recommended Citation
Wang, Xiao; Li, Xiangyang; Liang, Feng; and Zhang, Zhili
(2025)
"Research on Infrared and Visible Light Fusion Method Based on ResNet-50 and Laplacian Filtering,"
Journal of System Simulation: Vol. 37:
Iss.
12, Article 19.
DOI: 10.16182/j.issn1004731x.joss.25-FZ0696
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol37/iss12/19
First Page
3202
Last Page
3211
CLC
TP571
Recommended Citation
Wang Xiao, Li Xiangyang, Liang Feng, et al. Research on Infrared and Visible Light Fusion Method Based on ResNet-50 and Laplacian Filtering[J]. Journal of System Simulation, 2025, 37(12): 3202-3211.
DOI
10.16182/j.issn1004731x.joss.25-FZ0696
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