Laser & Optoelectronics Progress, Volume. 62, Issue 2, 0228001(2025)
Spatial Spectral VAFormer Graph Convolution Hyperspectral Image Super-Resolution Network
Fig. 6. Spectral information distribution of CAVE、Harvard dataset. (a) h1 image in Harvard dataset; (b) oil_painting image in CAVE dataset
Fig. 7. Heat map of correlation distribution between different spectral bands of CAVE、Harvard dataset
Fig. 8. Continuous density estimation between different spectral bands for CAVE dataset flower_ms
Fig. 9. Heatmap of spatial correlation between different patches of CAVE、Harvard dataset
Fig. 10. Comparison of absolute error plots for local zoom in the 10th channel of the CAVE data cloth_ms. (a) Grand truth; (b) CSTF; (c) UAL; (d) TSFN; (e) PZnet; (f) FF-former; (g) LGAR; (h) SSVF
Fig. 11. Comparison of absolute error plots for local zoom in the 10th channel of the Harvard data imga3. (a) Grand truth; (b) CSTF; (c) UAL; (d) TSFN; (e) PZnet; (f) FF-former; (g) LGAR; (h) SSVF
Fig. 12. Comparison of image element spectra at different positions of beads_ms for the CAVE dataset. (a) (160, 200); (b) (400, 400); (c) (200, 160)
Fig. 13. Comparison of image element spectra at different positions of imgh7 for the Harvard dataset. (a) (400, 500); (b) (400, 20); (c) (10, 10)
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Jiale Fan, Qiang Li, Ruifeng Zhang, Xin Guan. Spatial Spectral VAFormer Graph Convolution Hyperspectral Image Super-Resolution Network[J]. Laser & Optoelectronics Progress, 2025, 62(2): 0228001
Category: Remote Sensing and Sensors
Received: Apr. 3, 2024
Accepted: May. 10, 2024
Published Online: Jan. 7, 2025
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CSTR:32186.14.LOP241023