Xi Gong, Liang Wu, Zhong Xie, Zhanlong Chen, Yuanyuan Liu, Kan Yu. Classification Method of High-Resolution Remote Sensing Scenes Based on Fusion of Global and Local Deep Features[J]. Acta Optica Sinica, 2019, 39(3): 0301002
- Acta Optica Sinica
- Vol. 39, Issue 3, 0301002 (2019)
Fig. 1. Flow chart of GLDFB
Fig. 2. Network structure of VGG-19
Fig. 3. Reconstruction and coding of convolutional layer features
Fig. 4. Image examples of remote sensing scene. (a) UCM dataset; (b) SIRI dataset
Fig. 5. Time consumption for single iteration in k-means clustering process of 12 convolutional layer features under different K values. (a) UCM dataset; (b) SIRI dataset
Fig. 6. Classification accuracies of 12 convolutional layer features under different K values. (a) UCM dataset; (b) SIRI dataset
Fig. 7. Classification confusion matrix of GLDFB on UCM dataset
Fig. 8. Two kinds of misclassified scenes. (a) Road type; (b) building type
Fig. 9. Classification confusion matrix of GLDFB on SIRI dataset
Fig. 10. GLDFB results. (a) USGS large remote sensing image; (b) classification result
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Table 1. Output feature dimensions of VGG-19 convolutional layers
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Table 2. Average classification accuracy comparison of three kinds of convolutional layer features under different K values
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Table 3. Classification accuracies of several other features
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Table 4. Classification accuracy comparison of many kinds of features
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Table 5. Classification accuracy comparison on UCM dataset
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Table 6. Classification accuracy comparison on SIRI dataset
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Table 7. Classification results of GLDFB with other pre-training CNNs
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