Public
Active Thermography (IR) — 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 |
|---|---|---|---|
| emissivity_error | 0.94 – 0.97 | 0.955 | - |
| heat_source_power_drift | 0.98 – 1.04 | 1.01 | - |
| background_temperature | 24.0 – 27.0 | 25.5 | C |
| integration_time_offset | -0.02 – 0.04 | 0.01 | s |
InverseNet Baseline Scores
Method: CPU_baseline — Mismatch parameter: nominal
Scenario I (Ideal)
13.44 dB
SSIM 0.6187
Scenario II (Mismatch)
11.17 dB
SSIM 0.1544
Scenario III (Oracle)
18.72 dB
SSIM 0.1396
Per-scene breakdown (4 scenes)
| Scene | PSNR I | SSIM I | PSNR II | SSIM II | PSNR III | SSIM III |
|---|---|---|---|---|---|---|
| scene_00 | 13.33 | 0.6172 | 12.65 | 0.1296 | 18.68 | 0.1369 |
| scene_01 | 13.64 | 0.6232 | 9.57 | 0.1826 | 18.81 | 0.1378 |
| scene_02 | 13.41 | 0.6172 | 10.74 | 0.1609 | 18.65 | 0.1450 |
| scene_03 | 13.36 | 0.6172 | 11.71 | 0.1445 | 18.74 | 0.1385 |
Public Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | DiffusionThermo + gradient | 0.790 | 33.04 | 0.953 | 0.89 | ✓ Certified | Score-based diffusion for thermal imaging, 2024 |
| 2 | ThermoFormer + gradient | 0.777 | 32.42 | 0.947 | 0.87 | ✓ Certified | Transformer for thermography reconstruction, 2024 |
| 3 | PINN-Thermo + gradient | 0.754 | 30.6 | 0.926 | 0.89 | ✓ Certified | Raissi et al. 2019; thermography extension 2024 |
| 4 | U-Net Thermo + gradient | 0.737 | 29.4 | 0.907 | 0.9 | ✓ Certified | Fang et al., IEEE Trans. Instrum. Meas. 2023 |
| 5 | ThermoNet + gradient | 0.701 | 27.5 | 0.87 | 0.89 | ✓ Certified | Hu et al., NDT&E Int. 2024 |
| 6 | PnP-ADMM + gradient | 0.648 | 25.12 | 0.806 | 0.87 | ✓ Certified | Venkatakrishnan et al., IEEE GlobalSIP 2013 |
| 7 | PCT + gradient | 0.601 | 22.71 | 0.72 | 0.93 | ✓ Certified | Maldague & Marinetti, J. Appl. Phys. 1996 |
| 8 | TSR + gradient | 0.550 | 20.91 | 0.642 | 0.92 | ✓ Certified | Shepard, Thermosense 2001; Shepard et al., Opt. Eng. 2003 |
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%