Focus Fusion Network for Visible and Infrared Image Fusion

Image fusion techniques are commonly used to combine visible and infrared channels. The composite image should retain as much texture information from the visible channel and thermal information from the infrared channel as possible, while balancing these two features can be a challenge for practical applications. In this paper we propose a method for performing efficient and robust double-channel image fusion using self-attention and mutual cross-attention, along with a novel heatmap-based focusing loss to optimize the training process. The experimental results show that our approach significantly improves the details of fused images, and demonstrates the generalizability of our method under different scenes.