Hyperspectral Image Super Resolution

Hyperspectral image super-resolution (HSI-SR) aims to enhance the spatial resolution of hyperspectral images, which are rich in spectral information but often limited in spatial detail. Current research focuses on developing advanced deep learning models, including transformers and generative adversarial networks (GANs), often incorporating techniques like spectral unmixing and test-time training to overcome data scarcity and improve spectral fidelity. These advancements are significant because higher-resolution HSIs improve the accuracy of applications across diverse fields such as remote sensing, agriculture, and medical imaging, enabling more precise analysis and decision-making.