Spectral-Spatial Feature Tokenization Transformer for Hyperspectral Image Classification

• Published in: IEEE transactions on geoscience and remote sensing Vol. 60; pp. 1 - 14
• Main Authors: Sun, Le, Zhao, Guangrui, Zheng, Yuhui, Wu, Zebin
• Format: Journal Article
• Language: English
• Published: New York IEEE 2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Artificial neural networks; Classification; Coders; Computation; Computer applications; Convolution; Convolutional neural networks; Convolutional neural networks (CNNs); Data mining; Deep learning; Feature extraction; hyperspectral image (HSI) classification; Hyperspectral imaging; Image classification; Land cover; Machine learning; Methods; Modules; Neural networks; Principal component analysis; semantic features; Semantics; Spectra; spectral–spatial tokenization; transformer; Transformers

In hyperspectral image (HSI) classification, each pixel sample is assigned to a land-cover category. In the recent past, convolutional neural network (CNN)-based HSI classification methods have greatly improved performance due to their superior ability to represent features. However, these methods h...