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Fast Single Image Reflection Suppression via Convex Optimization

CVPR 2019 · Image generation › Image restoration · approach: Reflection removal · 74 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use the convex gradient-thresholding suppression model instead of Arvanitopoulos et al.Single-image reflection suppression · Synthetic images (four cases)PSNR: 20.87 -> 20.99; 16.80 -> 16.93; 19.42 -> 19.44; 15.10 -> 15.14Helped
Use the convex gradient-thresholding suppression model instead of Arvanitopoulos et al.Single-image reflection suppression · Synthetic images (four cases)SSIM: 0.896 -> 0.903; 0.716 -> 0.736; 0.896 -> 0.897; 0.787 -> 0.789Helped
Use the proposed direct convex solution instead of Li and BrownSingle-image reflection suppression · Synthetic images (four cases), 512 × 512execution time (sec): 12.06 -> 0.19; 11.68 -> 0.18; 7.25 -> 0.19; 7.69 -> 0.19Helped
Use the proposed direct convex solution instead of Li and BrownSingle-image reflection suppression · Real-world images (four cases), 1080 × 1440execution time (sec): 39.06 -> 1.46; 52.60 -> 1.36; 17.90 -> 1.40; 10.75 -> 1.15Helped
Increase gradient threshold h (ablation)Proposed reflection suppression model · Input imagesreflection suppressionMixed
Use a positive epsilon fidelity term to ensure uniqueness (ablation)Proposed convex model · Single-image reflection suppressionsolution uniquenessHelped
Use the proposed method when reflection edges are sharp and strongProposed reflection suppression model · Failure cases with sharp reflectionsreflection removalHurt

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