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11 July 2024 DCTDFusion: a dual-branch network based on dilated convolution and transformer for infrared and visible image fusion
Honggang Zhang, Haitao Yang, Fengjie Zheng, Haoyu Wang, Ningbo Guo, Yifan Xu
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Proceedings Volume 13210, Third International Symposium on Computer Applications and Information Systems (ISCAIS 2024); 132100U (2024) https://doi.org/10.1117/12.3035050
Event: Third International Symposium on Computer Applications and Information Systems (ISCAIS 2023), 2024, Wuhan, China
Abstract
Fusion of texture information and semantic information from visible and infrared images is important for many fields. However, existing algorithms extract features with a limited range of receptive fields which causes the loss of contextual information. This paper introduces DCTDFusion, a two-branch network integrating dilated convolution and Transformer to address this issue. We propose Residual Dilated Convolutions Block (RDCB) to extract local information of different receptive field ranges. To get the global information at multiple scales, we introduce the Transformer Dilated Convolutions Block. In addition, the Sobel feature extractor is used to retain the gradient information of both branches. Numerous experimental evidences show that the fused images of DCDTFusion contain rich information of significant targets and background in source images. Additionally, our method improves about 20%, 4%, 1% and 2% in MI, VIF, QAB/F and SSIM metrics comparing with the second best.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Honggang Zhang, Haitao Yang, Fengjie Zheng, Haoyu Wang, Ningbo Guo, and Yifan Xu "DCTDFusion: a dual-branch network based on dilated convolution and transformer for infrared and visible image fusion", Proc. SPIE 13210, Third International Symposium on Computer Applications and Information Systems (ISCAIS 2024), 132100U (11 July 2024); https://doi.org/10.1117/12.3035050
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KEYWORDS
Image fusion
Convolution
Transformers
Infrared imaging
Visible radiation
Infrared radiation
Feature extraction
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