Image Dehazing On Sots Outdoor
Metrics
PSNR
SSIM
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | PSNR | SSIM |
|---|---|---|
| generic-model-agnostic-convolutional-neural | 28.19 | 0.9638 |
| curricular-contrastive-regularization-for | 36.68 | 0.99 |
| griddehazenet-attention-based-multi-scale | 30.86 | 0.982 |
| mixdehazenet-mix-structure-block-for-image | 36.50 | 0.986 |
| enhanced-pix2pix-dehazing-network | 22.57 | 0.8630 |
| ffa-net-feature-fusion-attention-network-for | 33.57 | 0.9804 |
| strip-attention-for-image-restoration | 38.01 | 0.995 |
| exploring-the-potential-of-channel | 40.73 | 0.997 |
| selective-frequency-network-for-image | 40.05 | 0.996 |
| revitalizing-convolutional-network-for-image | 39.42 | 0.996 |
| uformer-a-general-u-shaped-transformer-for | 26.52 | 0.945 |
| u2-former-a-nested-u-shaped-transformer-for | 31.10 | 0.976 |
| unsupervised-single-image-dehazing-using-dark | 24.08 | 0.933 |
| focal-network-for-image-restoration | 37.71 | 0.995 |
| casdyf-net-image-dehazing-via-cascaded | 38.86 | 0.995 |
| dual-domain-strip-attention-for-image | 38.39 | 0.995 |
| mair-a-locality-and-continuity-preserving | 36.96 | 0.991 |
| omni-kernel-network-for-image-restoration | 37.68 | 0.995 |
| irnext-rethinking-convolutional-network | 39.18 | 0.996 |
| dea-net-single-image-dehazing-based-on-detail | 36.59 | 0.9897 |
| maxim-multi-axis-mlp-for-image-processing | 34.19 | - |
| aod-net-all-in-one-dehazing-network | 24.14 | 0.920 |
| image-restoration-via-frequency-selection | 40.40 | 0.997 |
| rethinking-performance-gains-in-image | 36.64 | 0.986 |
| onerestore-a-universal-restoration-framework | 35.58 | 0.9814 |
| an-ensemble-multi-scale-residual-attention | 25.81 | 0.9409 |
| gated-fusion-network-for-single-image | 22.30 | 0.880 |
| deep-energy-using-energy-functions-for | 24.07 | 0.933 |
| vision-transformers-for-single-image-dehazing | 34.95 | 0.984 |
| instruct-ipt-all-in-one-image-processing-1 | 39.95 | 0.992 |