Hidden
FPM — 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 |
|---|---|---|
| led_position | -0.07 – 0.23 | mm |
| na_error | 0.0965 – 0.1115 | |
| defocus | -1.4 – 4.6 | μm |
Hidden Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | Gradient Descent FPM + gradient | 0.643 | 25.08 | 0.805 | 0.85 | ✓ Certified | Tian & Waller, Optica 2015 |
| 2 | PtychoDV + gradient | 0.618 | 24.68 | 0.792 | 0.77 | ✓ Certified | Shamshad et al., IEEE TCI 2019 |
| 3 | Alternating Projections + gradient | 0.511 | 19.91 | 0.594 | 0.87 | ✓ Certified | Zheng et al., Nat. Photonics 2013 |
| 4 | Fourier PtychoNet + gradient | 0.455 | 18.84 | 0.542 | 0.75 | ✓ Certified | Jiang et al., BOE 2018 |
Dataset
Scenes: 5
Scoring Formula
0.4 × PSNR_norm + 0.4 × SSIM + 0.2 × (1 − ‖y − Ĥx̂‖/‖y‖)
PSNR: 40%
SSIM: 40%
Consistency: 20%