Chunhui ZHAO, Tong LI, Shou FENG. Hyperspectral Image Classification Based on Dense Convolution and Domain Adaptation[J]. Acta Photonica Sinica, 2021, 50(3): 148
- Acta Photonica Sinica
- Vol. 50, Issue 3, 148 (2021)
Fig. 1. Example of a DenseNet with four layers (i = 4)
Fig. 2. Subspace feature transformation
Fig. 3. Schematic of the hyperspectral image classification based on DCDA
Fig. 4. Schematic of the dense convolution-based embedding module (The number of convolutional layers is 3)
Fig. 5. Schematic of the discriminator module
Fig. 6. Source and target images in Indiana dataset
Fig. 7. Source and target images in Pavia dataset
Fig. 8. Source and target image spectral curves
Fig. 9. Classification result of target Indiana dataset
Fig. 10. Classification result of target Indiana dataset
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Table 1. Number of samples in the Indiana dataset and classification accuracy of each category
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Table 2. Comparison of classification accuracy in the Indiana dataset
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Table 3. Number of samples in the Pavia dataset and classification accuracy of each category
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Table 4. Comparison of classification accuracy in the Pavia dataset
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