Table 7 Quantitative comparison of different methods on the XiongAn dataset.

From: Cross-range self-attention single hyperspectral image super-resolution method based on U-Net architecture

Models

d

HR_image_size

\(\text {PSNR}\uparrow\)

\(\text {SSIM}\uparrow\)

\(\text {SAM}\downarrow\)

\(\text {ERGAS}\downarrow\)

\(\text {CC}\uparrow\)

Bicubic

4

256 × 256

41.4710

0.9300

2.5692

1.2958

0.9094

GDRRN

4

256 × 256

41.7875

0.9328

2.4682

1.2369

0.9156

Deep_hs_Prior

4

256 × 256

41.6732

0.9350

2.4228

1.2367

0.9160

SSPSR

4

256 × 256

42.3721

0.9334

2.3270

1.1712

0.9298

PDE-Net

4

256 × 256

42.4364

0.9399

2.3089

1.7413

0.9351

PUDPN

4

256 × 256

41.7357

0.9372

2.3891

1.2144

0.9217

CST

4

256 × 256

42.7059

0.9413

2.2135

1.1070

0.9364

Cs_Unet (Ours)

4

256 × 256

42.7382

0.9458

2.2114

1.1056

0.9367

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