16bit-from-8bit Image Reconstruction Model
This model reconstructs 16‑bit per channel images from standard 8‑bit input images. It is trained on paired 8‑bit and 16‑bit data and optimized to preserve color fidelity and high-frequency detail.
- Median MAE: 410
- Architecture Update: Added Leaky ReLU
- Training Resolution: 512×512 (Hand Selected Dataset 2k)
- Training Resolution: 1024×1024 (Hand Selected Dataset 500)
Dataset
- Total images: 54,580
- RAW patch images: 46,000 (~10 GB)
- 48‑bit synthetic images: 8,580 (~2 GB)
Evaluation Summary
| MAE Range | Accuracy Comment | Percent (%) |
|---|---|---|
| ≥1000 | Occasionally visible in uniform areas | 1.06 |
| 600–1000 | Almost never visible | 10.03 |
| 400–600 | Fully imperceptible | 27.39 |
| 200–400 | Near perfect | 59.95 |
| ≤200 | Near exact scientific | 1.57 |
Intended Use
Primary Use Cases
- Reconstruction of 16‑bit per channel images from 8‑bit input
- JPG & GIF post-processing and enhancement
- Archival and art restoration workflows
Not Intended For
- Lossless scientific measurement or precision tasks
- Medical AI enhancement