Yingyue Wu

Infrared polarization image fusion aims to generate a single image that integrates complementary information from both modalities to enhance scene perception. However, this task is hindered by significant modality gaps, high noise levels in polarization images, and the difficulty of preserving fine details from both sources. To address these challenges, we propose an end-to-end network, the feature-decoupled multi-scale Swin transformer (FDMSFuse).