---
language:
  - en
license: cc-by-nc-nd-4.0
tags:
  - image-to-image
  - 16bit-reconstruction
  - hdr
  - custom-vision
datasets:
  - custom-dataset-8bit-to-16bit
metrics:
  - name: Median MAE
    type: regression
    value: 410
  - name: LPIPS (Alex)
    type: perceptual
    value: 0.044
---

# 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 datasets and optimized to preserve color fidelity, structural consistency, and high-frequency detail.

- **Median MAE:** 410  
- **LPIPS (Alex):** ~0.044 (60-image evaluation)  
- **Architecture Update:** Added Leaky ReLU
- **Training Resolution:** 256×256(46k Patches from Raw HDR images with 8,580 48bit synthetic images.) 
- **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 @ 256x256 (~10 GB)  
  - **48-bit synthetic images:** 8,580 (~2 GB)

Addtional 10GB in Hand Selected RAW images, for the 512px and 1024px High Frequency Training Passes
---


### MAE Distribution (8-bit → 16-bit reconstruction)

| 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        |

### Perceptual Metrics (60-image test set)

| Metric              | Result  | Interpretation |
|-------------------|--------|----------------|
| LPIPS (Alex)       | 0.044  | Low perceptual distance / high similarity |
| Gradient Energy    | 0.088 → 0.108 | Preserved fine detail, slight sharpening |
| FFT Structure Score| 1.07 → 1.23 | Improved high-frequency retention |
| Histogram Continuity | 11.2 → 11.3 | Stable tonal distribution |

## Interpretation Summary

- LPIPS values (~0.03–0.07 range) indicate **high perceptual similarity**
- Structural metrics (FFT + gradients) show **consistent detail reconstruction**
- Histogram stability indicates **no major tonal drift between bit-depth conversions**

---

## 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