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A Physics-Based Noise Formation Model for Extreme Low-Light Raw Denoising
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Replace Gaussian-approximated shot noise with true Poisson shot noise (ablation) | G+P noise model · SID Sony | PSNR: 37.08 -> 38.31; 32.85 -> 34.39; 31.87 -> 33.37 | Helped |
| Use Tukey lambda rather than Gaussian read noise (ablation) | G+P* noise model · SID Sony | PSNR: 38.31 -> 39.10; 34.39 -> 36.46; 33.37 -> 35.69 | Helped |
| Add row noise (ablation) | G*+P* noise model · SID Sony | PSNR: 39.10 -> 39.23; 36.46 -> 36.89; 35.69 -> 36.01 | Helped |
| Add uniform quantization noise (ablation) | G*+P*+R noise model · SID Sony | PSNR: 39.23 -> 39.27; 36.89 -> 37.13; 36.01 -> 36.30 | Helped |
| Train with the full physics-based noise model instead of paired real data | U-Net · SID Sony | PSNR: 38.60 -> 39.27; 37.08 -> 37.13; 36.29 -> 36.30 | Mixed |
| Train with the calibrated physics-based noise model instead of paired real data | U-Net · ELD cameras | PSNR | Mixed |
| Use Gaussian read noise and Gaussian-approximated shot noise instead of the full model (ablation) | U-Net · SID Sony | PSNR: 39.27 -> 37.08; 37.13 -> 32.85; 36.30 -> 31.87 | Hurt |
Closest papers by meaning
- Physics-Guided ISO-Dependent Sensor Noise Modeling for Extreme Low-Light Photography (CVPR 2023 · similarity 0.91)
- Noise Modeling in One Hour: Minimizing Preparation Efforts for Self-supervised Low-Light RAW Image Denoising (CVPR 2025 · similarity 0.90)
- 2-Shots in the Dark: Low-Light Denoising with Minimal Data Acquisition (CVPR 2026 · similarity 0.89)
- Estimating Fine-Grained Noise Model via Contrastive Learning (CVPR 2022 · similarity 0.89)
- Realistic Noise Synthesis with Diffusion Models (AAAI 2025 · similarity 0.87)
- Real-World Mobile Image Denoising Dataset with Efficient Baselines (CVPR 2024 · similarity 0.86)
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