关键词: 高光谱遥感图像分类, 深度学习, 卷积神经网络（CNN）, 空谱特征

Abstract:

Hyperspectral Imagery（HSI） classification is an important task of hyperspectral image processing and application. With the development of deep learning, Convolutional Neural Network（CNN） has gradually become an effective solution to the classification problem of HSI. Firstly, the task of HSI classification is summarized, and the existing problems are analyzed. Secondly, CNN and its classification methods based on spectral features, spatial features and spatial-spectral features have been systematically sorted out, and the above classification methods are carried out experimental comparison. Finally, the key issues of HSI classification are summarized and future research directions are discussed.

Key words: hyperspectral image classification, deep learning, Convolutional Neural Network（CNN）, spatial-spectral features