PVSSNet: Progressive Feature Interaction Visual State-Space Network for Multispectral Pansharpening

Pansharpening involves extracting spectral information from multispectral images and structural details from panchromatic images, then fusing them to produce high-resolution multispectral remote sensing images. However, high-resolution multispectral images often suffer from spectral or structural information loss. In this paper, we introduce a pansharpening algorithm based on a Progressive Feature Interaction Visual State Space Network. It enables interaction between local and global features of multispectral and panchromatic images and facilitates the injection of spectral and spatial details through distinct attention modules. This approach effectively preserves both spectral characteristics and spatial structure through inter-branch information interaction and complementation. Additionally, by integrating a visual state space network, the proposed model achieves deep reconstruction of multi-scale global information, enhancing robustness and generalization. Extensive experimental results demonstrate that the proposed network achieves highly competitive performance in both visual assessments and objective metric evaluations.