Hidden

Stimulated Raman Scattering (SRS) Microscopy — Hidden Tier

(5 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
lock_in_phase_error -1.4 – 4.6 deg
cross_phase_modulation -0.7 – 2.3 -
laser_intensity_noise_(rin) -151.4 – -145.4 dBc/Hz

Hidden Tier Leaderboard

# Method Score PSNR SSIM Consistency Trust Source
1 PnP-DnCNN + gradient 0.604 23.61 0.754 0.83 ✓ Certified Zhang et al., 2017
2 PINN-Spectra + gradient 0.576 22.6 0.715 0.82 ✓ Certified Physics-informed neural network
3 CDAE + gradient 0.561 21.96 0.688 0.83 ✓ Certified Zhang et al., Sensors 2024
4 Cascade-UNet + gradient 0.542 21.19 0.654 0.84 ✓ Certified Physics-informed UNet, 2025
5 SpectraFormer + gradient 0.529 21.38 0.663 0.75 ✓ Certified Spectroscopy transformer, 2024
6 Baseline Correction + gradient 0.516 20.71 0.632 0.78 ✓ Certified Polynomial fitting baseline
7 SG-ALS + gradient 0.512 20.03 0.6 0.86 ✓ Certified Savitzky-Golay + ALS baseline
8 DiffusionSpectra + gradient 0.506 20.42 0.619 0.77 ✓ Certified Zhang et al., 2024
9 ScoreSpectra + gradient 0.505 19.9 0.594 0.84 ✓ Certified Wei et al., 2025
10 SVD + gradient 0.495 19.49 0.574 0.85 ✓ Certified Singular Value Decomposition
11 U-Net-Spectra + gradient 0.453 18.43 0.521 0.8 ✓ Certified Spectral U-Net variant

Dataset

Scenes: 5

Scoring Formula

0.4 × PSNR_norm + 0.4 × SSIM + 0.2 × (1 − ‖y − Ĥx̂‖/‖y‖)

PSNR: 40% SSIM: 40% Consistency: 20%
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