Hidden
Shearography — Hidden Tier
(3 scenes)Fully blind server-side evaluation — no data download.
What you get
No data downloadable. Algorithm runs server-side on hidden measurements.
How to use
Package algorithm as Docker container / Python script. Submit via link.
What to submit
Containerized algorithm accepting y + H, outputting x_hat + corrected spec.
Parameter Specifications
🔒
True spec hidden — blind evaluation, only ranges available.
| Parameter | Spec Range | Unit |
|---|---|---|
| shearing_amount_error | -1.4 – 4.6 | - |
| speckle_decorrelation | -0.042 – 0.138 | - |
| loading_non_uniformity | -2.8 – 9.2 | - |
Hidden Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | PhaseFormer + gradient | 0.608 | 24.2 | 0.776 | 0.78 | ✓ Certified | Phase unwrapping transformer, 2024 |
| 2 | ShearNet + gradient | 0.601 | 23.82 | 0.762 | 0.79 | ✓ Certified | Shearography DL reconstruction, 2022 |
| 3 | PnP-Phase + gradient | 0.522 | 20.91 | 0.642 | 0.78 | ✓ Certified | PnP with phase unwrapping prior |
| 4 | Goldstein MCF + gradient | 0.494 | 19.47 | 0.573 | 0.85 | ✓ Certified | Goldstein et al., Radio Sci. 1988 |
Dataset
Scenes: 3
Scoring Formula
0.4 × PSNR_norm + 0.4 × SSIM + 0.2 × (1 − ‖y − Ĥx̂‖/‖y‖)
PSNR: 40%
SSIM: 40%
Consistency: 20%