Hidden
SIM — Hidden Tier
(5 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 |
|---|---|---|
| pattern_phase | -0.035 – 0.115 | rad |
| pattern_freq | -0.7 – 2.3 | % |
| modulation_depth | -3.5 – 11.5 | % |
Hidden Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | SIMformer + gradient | 0.723 | 29.38 | 0.907 | 0.83 | ✓ Certified | SIM reconstruction transformer, 2024 |
| 2 | Wiener-SIM + gradient | 0.615 | 23.97 | 0.767 | 0.84 | ✓ Certified | Gustafsson, J. Microsc. 2000 |
| 3 | PnP-SIM + gradient | 0.600 | 24.01 | 0.769 | 0.76 | ✓ Certified | PnP with SIM forward model |
| 4 | DL-SIM + gradient | 0.584 | 22.81 | 0.724 | 0.83 | ✓ Certified | Jin et al., Nat. Methods 2023 |
Dataset
Scenes: 5
Scoring Formula
0.4 × PSNR_norm + 0.4 × SSIM + 0.2 × (1 − ‖y − Ĥx̂‖/‖y‖)
PSNR: 40%
SSIM: 40%
Consistency: 20%