Graph Relation Aggregated Spectral Perception Network for Hyperspectral Classification

Cross-domain few-shot hyperspectral image classification (CDFSL HSIC) presents significant challenges, primarily due to spectral variability across domains and the scarcity of labeled target samples. To tackle these issues, we propose a Graph Relation Aggregated Spectral Perception Network (GRASP-Net), which progressively models spectral and structural information from the sample level to the category level. First, an Enhanced Spectral Perception(ESP) module is developed to refine sample-level f