Grayscale Image Denoising On Bsd68 Sigma25
Metriken
PSNR
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Vergleichstabelle
| Modellname | PSNR |
|---|---|
| blind-universal-bayesian-image-denoising-with | 28.75 |
| trainable-nonlinear-reaction-diffusion-a | 28.92 |
| cdlnet-robust-and-interpretable-denoising | 29.26 |
| ffdnet-toward-a-fast-and-flexible-solution | 29.19 |
| beyond-a-gaussian-denoiser-residual-learning | 29.23 |
| kbnet-kernel-basis-network-for-image | 29.54 |
| real-image-denoising-with-feature-attention | 29.34 |
| multi-level-wavelet-cnn-for-image-restoration | 29.41 |
| neural-nearest-neighbors-networks | 29.3 |
| swinia-self-supervised-blind-spot-image | 29.17 |
| learning-deep-cnn-denoiser-prior-for-image | 29.15 |
| deep-graph-convolutional-image-denoising | 29.35 |
| non-local-recurrent-network-for-image | 29.41 |
| fast-and-interpretable-nonlocal-neural | 29.38 |
| adversarial-distortion-learning-for-medical | 29.50 |
| index-network | 29.06 |