Hyperspectral image (HSI) classification attempts to classify each pixel, which is an important means of obtaining land-cover knowledge. HSIs are cubic data with spectral–spatial knowledge and can generally be considered as sequential data alongside spectral dimension. Unlike convolutional neural networks (CNNs), which mainly focus on local relationship models in images, transformers have been shown to be a powerful structure for qualifying sequence data. However, it lacks the excellent ability of CNNs in establishing local relationships in im...
