Table 4. Real-number multi-scale training comparison. The red shows the best while the blue indicates the second-best performance.
Dataset | Testing scale\Trained scales | 2, 3, 4 PSNR/SSIM | 1.5, 2, 2.5, 3, 2.5, 4 PSNR/SSIM | 1.5, 1.75, 2, 2.25, 2.5, 2.75, 3, 3.25, 3.5, 3.75, 4 PSNR/SSIM | VDSR [4, 28] (2, 3, 4) PSNR/SSIM |
Set 5 | 1.5 | 40.40/0.9766 | 40.62/0.9771 | 40.59/0.9770 | 33.54/0.9503 |
1.75 | 38.81/0.9677 | 38.81/0.9677 | 38.82/0.9677 | 35.91/0.9572 |
2 | 37.52/0.9585 | 37.49/0.9584 | 37.49/0.9585 | 37.53/0.9587 |
2.25 | 36.40/0.9496 | 36.34/0.9495 | 36.37/0.9495 | 35.12/0.9416 |
2.5 | 35.39/0.9404 | 35.41/0.9406 | 35.45/0.9406 | 34.34/0.9325 |
2.75 | 34.66/0.9326 | 34.63/0.9327 | 34.68/0.9328 | 33.54/0.9265 |
3 | 33.85/0.9226 | 33.83/0.9226 | 33.86/0.9228 | 33.66/0.9213 |
3.25 | 33.18/0.9137 | 33.13/0.9137 | 33.20/0.9138 | 32.47/0.9080 |
3.5 | 32.64/0.9042 | 32.66/0.9045 | 32.69/0.9046 | 32.18/0.9006 |
3.75 | 32.00/0.8957 | 31.99/0.8955 | 31.98/0.8953 | 31.57/0.8914 |
4 | 31.48/0.8854 | 31.51/0.8852 | 31.50/0.8853 | 31.34/0.8838 |