Hidden
Passive Microwave Radiometry — Hidden Tier
(3 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 |
|---|---|---|
| antenna_beam_width_error | -0.07 – 0.23 | deg |
| receiver_gain_drift | 0.993 – 1.023 | - |
| brightness_temperature_offset | -0.28 – 0.92 | K |
| cross_polarization_leakage | -0.0028 – 0.0092 | - |
Hidden Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | MWR-Former + gradient | 0.578 | 23.06 | 0.733 | 0.77 | ✓ Certified | Microwave radiometry transformer, 2024 |
| 2 | RadioNet + gradient | 0.542 | 21.11 | 0.651 | 0.85 | ✓ Certified | Passive microwave CNN, 2022 |
| 3 | Tikhonov-SMOS + gradient | 0.506 | 20.22 | 0.609 | 0.8 | ✓ Certified | Anterrieu, IEEE TGRS 2004 |
| 4 | Backus-Gilbert + gradient | 0.490 | 19.62 | 0.58 | 0.81 | ✓ Certified | Backus & Gilbert, Geophys. J. 1968 |
Dataset
Scenes: 3
Scoring Formula
0.4 × PSNR_norm + 0.4 × SSIM + 0.2 × (1 − ‖y − Ĥx̂‖/‖y‖)
PSNR: 40%
SSIM: 40%
Consistency: 20%