Public
Passive Microwave Radiometry — 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 |
|---|---|---|---|
| antenna_beam_width_error | -0.1 – 0.2 | 0.05 | deg |
| receiver_gain_drift | 0.99 – 1.02 | 1.005 | - |
| brightness_temperature_offset | -0.4 – 0.8 | 0.2 | K |
| cross_polarization_leakage | -0.004 – 0.008 | 0.002 | - |
InverseNet Baseline Scores
Method: CPU_baseline — Mismatch parameter: nominal
Scenario I (Ideal)
6.10 dB
SSIM 0.0513
Scenario II (Mismatch)
6.10 dB
SSIM 0.0506
Scenario III (Oracle)
9.04 dB
SSIM 0.5406
Per-scene breakdown (4 scenes)
| Scene | PSNR I | SSIM I | PSNR II | SSIM II | PSNR III | SSIM III |
|---|---|---|---|---|---|---|
| scene_00 | 6.10 | 0.0509 | 6.10 | 0.0505 | 9.04 | 0.5407 |
| scene_01 | 6.10 | 0.0513 | 6.10 | 0.0507 | 9.04 | 0.5407 |
| scene_02 | 6.10 | 0.0517 | 6.10 | 0.0507 | 9.04 | 0.5406 |
| scene_03 | 6.10 | 0.0515 | 6.10 | 0.0506 | 9.04 | 0.5406 |
Public Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | RadioNet + gradient | 0.735 | 29.53 | 0.909 | 0.88 | ✓ Certified | Passive microwave CNN, 2022 |
| 2 | MWR-Former + gradient | 0.717 | 28.38 | 0.889 | 0.89 | ✓ Certified | Microwave radiometry transformer, 2024 |
| 3 | Backus-Gilbert + gradient | 0.541 | 20.6 | 0.627 | 0.92 | ✓ Certified | Backus & Gilbert, Geophys. J. 1968 |
| 4 | Tikhonov-SMOS + gradient | 0.514 | 19.87 | 0.592 | 0.89 | ✓ Certified | Anterrieu, IEEE TGRS 2004 |
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%