Table 1.
Quantitative evaluation on LOL synthetic and real dataset, in terms of PSNR and SSIM. The best results are in bold.
| Method | LOL-Syn | LOL-Real | ||
|---|---|---|---|---|
| PSNR↑ | SSIM↑ | PSNR↑ | SSIM↑ | |
| BIMEF | 17.20 | 0.7172 | 17.85 | 0.6526 |
| CRM | 18.91 | 0.7864 | 19.65 | 0.6623 |
| DHECE | 17.75 | 0.7800 | 14.64 | 0.4450 |
| Dong | 16.90 | 0.7487 | 17.26 | 0.5270 |
| EFF | 17.20 | 0.7127 | 17.85 | 0.6526 |
| LIME | 16.88 | 0.7762 | 15.24 | 0.4702 |
| MF | 17.50 | 0.7514 | 18.73 | 0.5590 |
| MBLLEN | 17.07 | 0.7301 | 17.86 | 0.7247 |
| JED | 17.48 | 0.7444 | 17.33 | 0.6654 |
| SRIE | 14.50 | 0.6163 | 17.34 | 0.6859 |
| RRM | 17.15 | 0.7277 | 17.33 | 0.5144 |
| DRD | 17.13 | 0.7978 | 15.47 | 0.5672 |
| DeepUPE | 15.08 | 0.6225 | 13.27 | 0.4521 |
| SCIE | 18.50 | 0.7631 | 19.40 | 0.6906 |
| KinD | 17.84 | 0.7971 | 20.73 | 0.8103 |
| EnlightenGAN | 16.57 | 0.7338 | 18.23 | 0.6165 |
| RetinexNet | 22.05 | 0.9054 | 20.06 | 0.8158 |
| KinD++ | 17.69 | 0.8334 | 21.30 | 0.8226 |
| DRBN | 23.22 | 0.9275 | 20.29 | 0.8310 |
| Our | 24.62 | 0.9314 | 21.64 | 0.8481 |