In general, the goal of existing infrared and visible image fusion (IVIF) methods is to make the fused image contain both the high-contrast regions of the infrared image and the texture details of the visible image. Also, a hybrid loss function constructed with weight fidelity loss, gradient loss, and decoupling loss which ensures the fusion image to be generated to effectively preserves the source image’s texture details and luminance information.
This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.
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| Category | 🤖 Artificial Intelligence |
| Published | Jan 01, 2022 |
| Journal | IEEE Transactions on Instrumentation and Measurement |
| Authors | Xue Wang, Zheng Guan, Shishuang Yu, Jinde Cao, Ya Li |
| DOI | 10.1109/tim.2022.3216413 |
| Citations | 964 |
| Source | OpenAlex |