Decomposition-driven Multi-level Feature Fusion Framework for Infrared and Visible Image Fusion

This paper proposes a novel infrared and visible image fusion method based on the feature decomposition and the Multi-level Feature Fusion. Firstly, modal features are initially extracted and decomposed into unique features with disparate foreground information and common features with similar background information to better discern the background to be maintained and the foreground to be emphasized. Then, the multi-level features are extracted and fused, thus the target image contains detailed and semantic information in low-level and high-level features respectively. Finally, the fused multi-level feature is reconstructed to the target image. Experiments on public datasets M3FD and MSRS show that the proposed method is better than other latest methods.