Laser & Optoelectronics Progress, Volume. 57, Issue 12, 122803(2020)
Hyperspectral Image Classification Based on Dual-Channel Dilated Convolution Neural Network
Fig. 1. Structure diagram of the proposed framework
Fig. 2. Schematic of 1D dilated convolution. (a) Standard convolution; (b) dilated convolution
Fig. 3. DCD-CNN structure
Fig. 4. OA accuracy of different datasets at different λ values
Fig. 5. Classification maps of different methods on Indian Pines dataset. (a) Ground truth; (b) SVM; (c) AEAP; (d) DCNN; (e) FEFCN-ELM; (f) proposed method
Fig. 6. Classification maps of different methods on Pavia University dataset. (a) Ground truth; (b) SVM; (c) AEAP; (d) DCNN; (e) FEFCN-ELM; (f) proposed method
|
|
Get Citation
Copy Citation Text
Li Hu, Rui Shan, Fang Wang, Guoqian Jiang, Jingyi Zhao, Zhi Zhang. Hyperspectral Image Classification Based on Dual-Channel Dilated Convolution Neural Network[J]. Laser & Optoelectronics Progress, 2020, 57(12): 122803
Category: Remote Sensing and Sensors
Received: Oct. 1, 2019
Accepted: Oct. 29, 2019
Published Online: Jun. 3, 2020
The Author Email: Zhao Jingyi (zjylwsr@126.com)