DIR-HSI: Degradation-Invariant Representation Learning for Hyperspectral Image Classification (opens in new tab)

In recent years, hyperspectral image (HSI) classification has achieved remarkable progress in fine-grained surface recognition and intelligent remote sensing analysis. However, real-world degradations—such as sensor noise, compression artifacts, and atmospheric interference—often introduce severe domain shifts, leading to degraded robustness and limited generalization of existing models. To address this challenge, we propose DIR-HSI, a degradation-invariant hyperspectral classification framew...