Acta Optica Sinica, Volume. 39, Issue 10, 1028002(2019)
Hyperspectral Image Classification Algorithm Based on Two-Channel Generative Adversarial Network
The existing hyperspectral image generative adversarial network(GAN) classification algorithm cannot fully extract spectral and spatial-spectral features, which leads to the degradation of hyperspectral image classification accuracy. To resolve this issue, this study proposes a hyperspectral image classification algorithm based on a two-channel GAN. Improved one- and two-dimensional GAN classification frameworks are used to extract complete spectral and spatial-spectral features, respectively. Those features are nonlinearly fused to form a more comprehensive spatial-spectral features for classification. The experiments on two commonly used hyperspectral image datasets show that the proposed algorithm achieves the best classification accuracy; further, the results verify the effectiveness and advantages of the proposed algorithm.
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Xiaojun Bi, Zeyu Zhou. Hyperspectral Image Classification Algorithm Based on Two-Channel Generative Adversarial Network[J]. Acta Optica Sinica, 2019, 39(10): 1028002
Category: Remote Sensing and Sensors
Received: Feb. 22, 2019
Accepted: Jun. 21, 2019
Published Online: Oct. 17, 2019
The Author Email: Zhou Zeyu (zhouzeyu100@hrbeu.edu.cn)