Dev
Hyperspectral Remote Sensing — Dev Tier
(3 scenes)Blind evaluation tier — no ground truth available.
What you get
Measurements (y), ideal forward operator (H), and spec ranges only.
How to use
Apply your pipeline from the Public tier. Use consistency as self-check.
What to submit
Reconstructed signals and corrected spec. Scored server-side.
Parameter Specifications
🔒
True spec hidden — estimate parameters from spec ranges below.
| Parameter | Spec Range | Unit |
|---|---|---|
| spectral_shift | -0.48 – 0.72 | nm |
| smile_distortion | -0.24 – 0.36 | px |
| keystone_distortion | -0.12 – 0.18 | px |
| radiometric_gain | 0.976 – 1.036 | - |
Dev Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | MST++ + gradient | 0.729 | 29.16 | 0.903 | 0.88 | ✓ Certified | Cai et al., CVPRW 2022 |
| 2 | DBIN + gradient | 0.629 | 24.76 | 0.794 | 0.82 | ✓ Certified | Dong et al., CVPR 2021 |
| 3 | CNMF + gradient | 0.613 | 24.15 | 0.774 | 0.81 | ✓ Certified | Yokoya et al., IEEE TGRS 2012 |
| 4 | PnP-LTTR + gradient | 0.583 | 22.48 | 0.71 | 0.87 | ✓ Certified | He et al., IEEE TGRS 2020 |
Visible Data Fields
y
H_ideal
spec_ranges
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%