Public
Ghost Imaging — Public Tier
(3 scenes)Full-access development tier with all data visible.
What you get
Measurements (y), ideal forward operator (H), spec ranges, ground truth (x_true), and true mismatch spec.
How to use
Load HDF5 → compare reconstruction vs x_true → check consistency → iterate.
What to submit
Reconstructed signals (x_hat) and corrected spec as HDF5.
Parameter Specifications
✓
True spec visible — use these exact values for Scenario III oracle reconstruction.
| Parameter | Spec Range | True Value | Unit |
|---|---|---|---|
| bucket_detector_efficiency | 0.8 – 1.1 | 0.95 | - |
| speckle_correlation_mismatch | -2.0 – 4.0 | 1.0 | - |
| background_counts | -1.0 – 2.0 | 0.5 | - |
| number_of_measurements | -8000.0 – 46000.0 | 19000.0 | - |
InverseNet Baseline Scores
Method: CPU_baseline — Mismatch parameter: nominal
Scenario I (Ideal)
8.23 dB
SSIM 0.0225
Scenario II (Mismatch)
8.22 dB
SSIM 0.0224
Scenario III (Oracle)
8.12 dB
SSIM 0.0204
Per-scene breakdown (4 scenes)
| Scene | PSNR I | SSIM I | PSNR II | SSIM II | PSNR III | SSIM III |
|---|---|---|---|---|---|---|
| scene_00 | 5.83 | 0.0079 | 5.79 | 0.0078 | 5.94 | 0.0051 |
| scene_01 | 6.13 | 0.0023 | 6.14 | 0.0024 | 5.98 | 0.0025 |
| scene_02 | 5.80 | 0.0183 | 5.80 | 0.0183 | 5.79 | 0.0200 |
| scene_03 | 15.18 | 0.0613 | 15.17 | 0.0612 | 14.79 | 0.0539 |
Public Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | ScoreQuantum + gradient | 0.725 | 28.48 | 0.891 | 0.92 | ✓ Certified | Wei et al., 2025 |
| 2 | Ghost-ViT + gradient | 0.705 | 27.8 | 0.877 | 0.88 | ✓ Certified | Zhu et al., 2025 |
| 3 | Quantum-ViT + gradient | 0.685 | 26.86 | 0.855 | 0.87 | ✓ Certified | Quantum imaging transformer, 2024 |
| 4 | DRU-Net + gradient | 0.678 | 26.63 | 0.849 | 0.86 | ✓ Certified | Wang et al., Sci. Rep. 2020 |
| 5 | Quantum-CNN + gradient | 0.676 | 26.32 | 0.841 | 0.88 | ✓ Certified | Quantum imaging CNN |
| 6 | DiffusionQuantum + gradient | 0.628 | 24.12 | 0.773 | 0.89 | ✓ Certified | Zhang et al., 2024 |
| 7 | Bayesian CS + gradient | 0.600 | 23.16 | 0.737 | 0.87 | ✓ Certified | Bayesian compressed sensing |
| 8 | CS-TVAL3 + gradient | 0.581 | 22.17 | 0.697 | 0.9 | ✓ Certified | Li et al., 2014 |
| 9 | Photon Counting + gradient | 0.560 | 21.12 | 0.651 | 0.94 | ✓ Certified | Classical baseline |
| 10 | G(2)-Corr + gradient | 0.483 | 18.9 | 0.545 | 0.88 | ✓ Certified | Pittman et al., PRA 1995 |
Visible Data Fields
y
H_ideal
spec_ranges
x_true
true_spec
Dataset
Format: HDF5
Scenes: 3
Scoring Formula
0.4 × PSNR_norm + 0.4 × SSIM + 0.2 × (1 − ‖y − Ĥx̂‖/‖y‖)
PSNR: 40%
SSIM: 40%
Consistency: 20%