Adams-based hierarchical features fusion network for image dehazing

Shibai Yin, Shuhao Hu, Yibin Wang, Weixing Wang, Yee-Hong Yang

Abstract: Highlights•We propose the Adams-based Hierarchical Feature Fusion Network (AHFFN) for image dehazing.•The Adams Module is designed based on Adams Blocks, inspired by multi-step high-order Adams–Bashforth methods.•HFF and LSA are proposed to fuse features and pay attention to heavy haze pixels within and among the Adams Module.