Figure 1.
Figure 2.
Figure 3.
Figure 4.
Figure 5.
Figure 6.
Figure 7.
Figure 8.
PARAMETER CONFIGURATION OF THE VIT-BASE MODULE
| Module Component | Key Parameters | Main Function |
|---|---|---|
| Patch Embedding | Input Size:64×64×64 | Divide the feature map into 64 patches to reduce computational complexity. |
| Patch Size:8×8 | ||
| Output Dimension:768 | ||
| Multi-Head Attention | Number of Heads:12 | Establish global correlations to enhance complex feature modeling. |
| Dimension per Head:64 | ||
| Feed-Forward Network | MLP Structure:768→3072→768 | Perform nonlinear transformations of features to stabilize training in conjunction with LayerNorm. |
| Activation Function:GeLU | ||
| Residual Connection | Application Position:After each MSA/FFN sublayer | Prevent gradient vanishing and accelerate convergence. |
| Stacked Structure | Number of Encoder Layers:12 | Construct a deep feature transformer to improve global context modeling capabilities. |
| Total Parameters:86M |
COMPARISON OF PSNR (DB) / SSIM FOR DIFFERENT METHODS ON BENCHMARK DATASETS UNDER ×2 AND ×4 SUPER-RESOLUTION
| Multiple | Model | Set5 | Set14 | BSD100 | Urban100 |
|---|---|---|---|---|---|
| ×2 | SRCNN | 36.66/0.9542 | 32.42/0.9063 | 31.36/0.8918 | 29.50/0.8946 |
| EDSR | 38.11/0.9603 | 33.92/0.9180 | 32.46/0.9015 | 32.93/0.9355 | |
| RCAN | 38.31/0.9614 | 34.15/0.9209 | 32.63/0.9027 | 33.34/0.9410 | |
| HAN | 38.34/0.9618 | 34.18/0.9214 | 32.68/0.9032 | 33.41/0.9422 | |
| NLSA | 38.35 / 0.9620 | 34.20 / 0.9217 | 32.69 / 0.9036 | 33.48 / 0.9430 | |
| SwinIR | 38.40 / 0.9624 | 34.25 / 0.9221 | 32.71 / 0.9040 | 33.57 / 0.9438 | |
| Our | 38.51 / 0.963 | 34.40 / 0.9235 | 32.85 / 0.9054 | 33.95 / 0.9465 | |
| ×4 | SRCNN | 30.49 / 0.8630 | 27.50 / 0.7510 | 26.91 / 0.7105 | 24.54 / 0.7260 |
| EDSR | 32.65 / 0.9000 | 28.95 / 0.7918 | 27.80 / 0.7449 | 26.98 / 0.8085 | |
| RCAN | 32.78 / 0.9004 | 29.06 / 0.7932 | 27.89 / 0.7468 | 27.14 / 0.8125 | |
| HAN | 32.80 / 0.9008 | 29.08 / 0.7939 | 27.91 / 0.7473 | 27.24 / 0.8140 | |
| NLSA | 32.82 / 0.9010 | 29.10 / 0.7942 | 27.93 / 0.7480 | 27.31 / 0.8153 | |
| SwinIR | 32.88 / 0.9014 | 29.14 / 0.7948 | 27.96 / 0.7488 | 27.45 / 0.8165 | |
| Our | 33.00 / 0.9025 | 29.28 / 0.7962 | 28.10 / 0.7505 | 27.73 / 0.8200 |