Laser & Optoelectronics Progress, Volume. 62, Issue 2, 0228001(2025)

Spatial Spectral VAFormer Graph Convolution Hyperspectral Image Super-Resolution Network

Jiale Fan*, Qiang Li, Ruifeng Zhang, and Xin Guan
Author Affiliations
  • School of Microelectronics, Tianjin University, Tianjin 300072, China
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    Figures & Tables(18)
    SSVF model schematic
    Architecture of composite graph convolution module
    Schematic of multiscale mix convolution module
    Architecture of VAFormer
    Spatial distribution diagram of pixels in CAVE、Harvard dataset
    Spectral information distribution of CAVE、Harvard dataset. (a) h1 image in Harvard dataset; (b) oil_painting image in CAVE dataset
    Heat map of correlation distribution between different spectral bands of CAVE、Harvard dataset
    Continuous density estimation between different spectral bands for CAVE dataset flower_ms
    Heatmap of spatial correlation between different patches of CAVE、Harvard dataset
    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
    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
    Comparison of image element spectra at different positions of beads_ms for the CAVE dataset. (a) (160, 200); (b) (400, 400); (c) (200, 160)
    Comparison of image element spectra at different positions of imgh7 for the Harvard dataset. (a) (400, 500); (b) (400, 20); (c) (10, 10)
    • Table 1. Effect of spatial correlation threshold on the model when the spectral correlation threshold is 0.2

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      Table 1. Effect of spatial correlation threshold on the model when the spectral correlation threshold is 0.2

      IndicatorSpatial correlation threshold
      0.20.40.60.8
      PSNR51.24451.29251.29950.172
      SSIM0.99640.99640.99640.9958
      SAM1.7031.6811.6261.833
      MSE0.00280.00280.00280.0030
    • Table 2. Effect of spectral correlation threshold on the model when the spatial correlation threshold is 0.6

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      Table 2. Effect of spectral correlation threshold on the model when the spatial correlation threshold is 0.6

      IndicatorSpectral correlation threshold
      0.20.40.60.8
      PSNR51.29951.20450.87149.106
      SSIM0.99640.99620.99590.9952
      SAM1.6261.7101.7661.997
      RMSE0.00280.00280.00300.0033
    • Table 3. Ablation studies by component

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      Table 3. Ablation studies by component

      ModuleIndicator
      PANRSSIMSAMRMSE
      None47.86500.99412.10700.0039
      MMC50.38700.99521.92500.0031
      VAFormer50.17100.99501.83100.0031
      VAFormer+CGC50.94400.99561.70300.0029
      MMC+VAFormer+CGC51.29900.99641.62600.0028
    • Table 4. Results of different scale factors comparison algorithms on CAVE dataset

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      Table 4. Results of different scale factors comparison algorithms on CAVE dataset

      FactorIndicatorCSTFUALTSFNPZnetFF-formerLGARSSVF
      ×4PSNR42.30043.96448.85350.28849.18650.97951.299
      SSIM0.96440.99200.99480.99560.99530.99600.9964
      SAM7.7163.0421.8691.9821.9971.8331.781
      RMSE0.00900.00780.00460.00340.00350.00280.0028
      ×8PSNR41.71742.58549.26649.65449.10849.73350.211
      SSIM0.96650.99100.99430.99450.99540.99470.9949
      SAM7.5023.8992.3112.1892.2692.1081.965
      RMSE0.00970.00900.00380.00370.00380.00370.0037
      ×16PSNR39.82440.10546.53346.99446.32246.91547.041
      SSIM0.96330.98860.99220.99200.99300.99220.9928
      SAM7.3294.2572.9212.6812.9612.8402.772
      RMSE0.01460.01130.00580.00570.00580.00570.0057
    • Table 5. Results of different scale factors comparison algorithms on Harvard dataset

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      Table 5. Results of different scale factors comparison algorithms on Harvard dataset

      FactorIndicatorCSTFUALTSFNPZnetFF-formerLGARSSVF
      ×4PSNR42.36244.85348.99349.38248.85649.41149.762
      SSIM0.97220.98650.98740.98730.98730.98740.9879
      SAM8.2574.7623.4883.2503.4223.3113.135
      RMSE0.00900.00690.00380.00360.00380.00360.0036
      ×8PSNR41.23343.36848.66148.86448.20348.83549.014
      SSIM0.97060.98370.98500.98490.98500.98500.9860
      SAM9.2145.0113.7633.9013.9553.8583.351
      RMSE0.00970.00860.00390.00380.00410.00380.0038
      ×16PSNR39.82242.56347.29947.23246.95847.23547.255
      SSIM0.95210.97880.98030.98010.98030.98030.9827
      SAM9.6215.8124.3444.2194.4254.2684.221
      RMSE0.01460.01130.00580.00570.00580.00570.0057
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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

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    Paper Information

    Category: Remote Sensing and Sensors

    Received: Apr. 3, 2024

    Accepted: May. 10, 2024

    Published Online: Jan. 7, 2025

    The Author Email:

    DOI:10.3788/LOP241023

    CSTR:32186.14.LOP241023

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