期刊
INFRARED PHYSICS & TECHNOLOGY
卷 104, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.infrared.2019.103144
关键词
Image fusion; Infrared image processing; Generative adversarial network (GAN); Local binary patterns (LBP)
资金
- National Natural Science Foundation of China [61434004]
- Tianjin Research Program of Application Foundation and Advanced Technology [17ZXRGGX00040]
This paper proposes a novel generative adversarial network (GAN) architecture to fuse infrared (IR) and visible images (VIS), named as LBP-BEGAN. The fused images generated by this network have rich boundary information through a loss function based on local binary patterns (LBP). At the same time, a distribution-based discriminator is applied to distinguish the fused images and the original IR and VIS images to guarantee the quality of the fusion results. This structure is able to establish adversarial loss without an ideal-fused image as the label. Qualitative and quantitative comparisons against eight classical and state-of-the-art fusion methods demonstrate the effectiveness of our strategy. Our approach can generate fused images with clear edges and textures and successfully preserves a large amount of information in the original images.
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