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Burst Image Restoration and Enhancement

CVPR 2022 · Image generation › Image restoration · approach: Real-world restoration with unaligned data · 102 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use BIPNet instead of MFIRBurst super-resolution · SyntheticBurst ×4PSNR: 41.56 -> 41.93Helped
Use BIPNet instead of MFIRBurst super-resolution · BurstSR ×4PSNR: 48.33 -> 48.49Helped
Use BIPNet instead of KaradenizBurst low-light enhancement · SID SonyPSNR: 29.80 -> 32.87Helped
Use BIPNet instead of MFIRBurst denoising · Grayscale burst denoisingPSNR (Average): 34.74 -> 36.81Helped
Use BIPNet instead of MFIRBurst denoising · Color burst denoisingPSNR (Average): 37.40 -> 38.74Helped
Add FPM to the baseline (ablation)BIPNet · SyntheticBurst ×4 ablationPSNR: 36.38 -> 36.54Helped
Add DAM (ablation)BIPNet · SyntheticBurst ×4 ablationPSNR: 36.54 -> 38.39Helped
Add RAF (ablation)BIPNet · SyntheticBurst ×4 ablationPSNR: 38.39 -> 39.10Helped
Add PBFF (ablation)BIPNet · SyntheticBurst ×4 ablationPSNR: 39.10 -> 39.64Helped
Add MSF (ablation)BIPNet · SyntheticBurst ×4 ablationPSNR: 39.64 -> 40.35Helped
Add AGU (ablation)BIPNet · SyntheticBurst ×4 ablationPSNR: 40.35 -> 41.25Helped
Add EBFA (ablation)BIPNet · SyntheticBurst ×4 ablationPSNR: 41.25 -> 41.55Helped

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