MURF: Mutually Reinforcing Multi-Modal Image Registration and Fusion

Existing image fusion methods are typically limited to aligned source images and have to "tolerate" parallaxes when images are unaligned. Simultaneously, the large variances between different modalities pose a significant challenge for multi-modal image registration. This study proposes a novel method called MURF, where for the first time, image registration and fusion are mutually reinforced rather than being treated as separate issues. MURF leverages three modules: shared information extraction module (SIEM), multi-scale coarse registration module (MCRM), and fine registration and fusion module (F2M). The registration is carried out in a coarse-to-fine manner. During coarse registration, SIEM first…

• NN
  National Natural Science Foundation of China

  Award: 62276192