Grayscale Image Denoising On Bsd68 Sigma15
Metrics
PSNR
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | PSNR |
|---|---|
| deep-graph-convolutional-image-denoising | 31.83 |
| real-image-denoising-with-feature-attention | 31.81 |
| kbnet-kernel-basis-network-for-image | 31.98 |
| learning-deep-cnn-denoiser-prior-for-image | 31.63 |
| blind-universal-bayesian-image-denoising-with | 31.35 |
| ffdnet-toward-a-fast-and-flexible-solution | 31.63 |
| swinir-image-restoration-using-swin | 31.97 |
| non-local-recurrent-network-for-image | 31.88 |
| trainable-nonlinear-reaction-diffusion-a | 31.42 |
| adversarial-distortion-learning-for-medical | 32.11 |
| cdlnet-robust-and-interpretable-denoising | 31.74 |
| fast-and-interpretable-nonlocal-neural | 31.82 |
| swinia-self-supervised-blind-spot-image | 31.07 |
| multi-level-wavelet-cnn-for-image-restoration | 31.86 |
| index-network | 31.23 |
| restormer-efficient-transformer-for-high | 31.96 |