Metrics are evaluated on different full-color datasets such as
- Kodak
http://r0k.us/graphics/kodak/ https://github.com/MohamedBakrAli/Kodak-Lossless-True-Color-Image-Suite - McMaster https://www4.comp.polyu.edu.hk/~cslzhang/CDM_Dataset.htm
To run the evaluation, make each dataset a folder and run
python -m debayer.apps.eval <Database-Path> --methods all
Note, in case the latest version below does not match the current version of pytorch-debayer, performance statistics to remain unchanged.
The PSNR (Peak-Signal-Noise-Ratio) values (dB, higher is better) of each channel (R, G, B) and PSNR of the whole image (RGB) across 2 Datasets (Kodak, McMaster) and for each algorithm.
| Database | Method | R (dB) | G (dB) | B (dB) | PSNR (dB) |
|---|---|---|---|---|---|
| Kodak | Debayer2x2 | 26.64 | 28.18 | 26.98 | 27.27 |
| Debayer3x3 | 28.18 | 32.66 | 28.86 | 29.90 | |
| Debayer5x5 | 33.84 | 38.05 | 33.53 | 35.14 | |
| DebayerSplit | 26.64 | 32.66 | 26.98 | 28.76 | |
| OpenCV | 28.15 | 31.25 | 28.62 | 29.34 | |
| McMaster | Debayer2x2 | 28.47 | 30.32 | 28.63 | 29.14 |
| Debayer3x3 | 31.68 | 35.40 | 31.25 | 32.78 | |
| Debayer5x5 | 34.04 | 37.62 | 33.02 | 34.89 | |
| DebayerSplit | 28.47 | 35.40 | 28.63 | 30.83 | |
| OpenCV | 31.64 | 35.22 | 31.22 | 32.69 |