Laser & Optoelectronics Progress, Volume. 60, Issue 10, 1028004(2023)
Non-Subsampling Shearlet Transform Remote Sensing Image Fusion with Improved Dual-channel Adaptive Pulse Coupled Neural Network
Fig. 1. Frequency domain subdivision diagram and support interval of NSST. (a) Frequency domain subdivision map; (b) frequency domain support interval
Fig. 2. Architecture of DC-PCNN
Fig. 3. Fusion results of high-frequency coefficients in all directions. (a)-(b) High frequency subbands in 2 directions in first layer; (c)-(f) high frequency subbands in 4 directions in second layer
Fig. 4. Direction information calculation
Fig. 5. Flow chart
Fig. 6. Influence of decomposition layers on fusion effect
Fig. 7. First group of experimental data. (a) MS; (b) PAN
Fig. 8. Fusion results of first group. (a) SE; (b) NSCT; (c) ISCM; (d) WDCPAPCNN; (e) PAPCNN; (f) proposed method
Fig. 9. Second group of experimental data. (a) MS; (b) PAN
Fig. 10. Fusion results of second group. (a) SE; (b) NSCT; (c) ISCM; (d) WDCPAPCNN; (e) PAPCNN; (f) proposed method
Fig. 11. Third group of experimental data. (a) MS; (b) PAN
Fig. 12. Fusion results of third group. (a) SE; (b) NSCT; (c) ISCM; (d) WDCPAPCNN; (e) PAPCNN; (f) proposed method
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Linian Ruan, Yan Dong. Non-Subsampling Shearlet Transform Remote Sensing Image Fusion with Improved Dual-channel Adaptive Pulse Coupled Neural Network[J]. Laser & Optoelectronics Progress, 2023, 60(10): 1028004
Category: Remote Sensing and Sensors
Received: Nov. 3, 2021
Accepted: Feb. 14, 2022
Published Online: May. 17, 2023
The Author Email: Dong Yan (dongyanchina@sina.com)