ReFusion: Learning Image Fusion from Reconstruction with Learnable Loss via Meta-Learning

arXiv:2312.07943v2 Announce Type: replace
Abstract: Image fusion aims to combine information from multiple source images into a single one with more comprehensive informational content. The significant challenges for deep learning-based image fusion algorithms are the lack of a definitive ground truth as well as the corresponding distance measurement, with current manually given loss functions constrain the flexibility of model and generalizability for unified fusion tasks. To overcome these limitations, we introduce a unified image fusion framework based on meta-learning, named …

abstract algorithms arxiv challenges cs.cv deep learning fusion image images information loss measurement meta meta-learning multiple truth type via