CCHD: Chain Connection and Hybrid Dense Attention for Remote Sensing Dehazing
Sen Lin, Mengzhao Liu, Shiben Liu · IEEE Geoscience and Remote Sensing Letters · 2025
In the process of dehazing of remote sensing images, the problems of haze residue and color overcompensation often occur. To address these problems, we propose a novel remote sensing dehazing network based on chain connection and hybrid dense attention. First, we propose a hybrid attention block used to enhance the network’s ability to extract intrinsic structural and textural features of remote sensing images. We design the chain connection mechanism to achieve effective feature information transmission, which has the advantage of expanding the network width while reducing the parameters. Then, we develop the feature fusion block for deep fusion of multi-level and multiscale remote sensing image feature maps. Finally, we employ a gradient-guided block to recover edge details and reduce geometric deformation. The experimental results show that our dehazing algorithm performs state-of-the-art methods in both subjective visual evaluation and objective evaluation indexes.