U2Fusion: A Unified Unsupervised Image Fusion Network

This study proposes a novel unified and unsupervised end-to-end image fusion network, termed as U2Fusion, which is capable of solving different fusion problems, including multi-modal, multi-exposure, and multi-focus cases. Using feature extraction and information measurement, U2Fusion automatically estimates the importance of corresponding source images and comes up with adaptive information preservation degrees. Hence, different fusion tasks are unified in the same framework. Based on the adaptive degrees, a network is trained to preserve the adaptive similarity between the fusion result and source images. Therefore, the stumbling blocks in applying deep learning for image fusion, e.g., the requirement of…

• NN
  National Natural Science Foundation of China

  Awards: 61772512, 61773295, 61971165
• NS
  Natural Science Foundation of Hubei Province

  Award: 2019CFA037