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When Color Constancy Goes Wrong: Correcting Improperly White-Balanced Images

CVPR 2019 · Image generation › Image restoration · approach: Image harmonization and color transformation · 148 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use the data-driven nearest-neighbor color mapping instead of diagonal WB correction on linearized sRGBImproperly white-balanced images · Intrinsic set (Set 1)MSE (Mean): 130.01 -> 77.79Helped
Use the data-driven nearest-neighbor color mapping instead of diagonal WB correction on linearized sRGBImproperly white-balanced images · Intrinsic set (Set 1)MAE (Mean): 4.29° -> 3.06°Helped
Use the data-driven nearest-neighbor color mapping instead of diagonal WB correction on linearized sRGBImproperly white-balanced images · Intrinsic set (Set 1)ΔE 2000 (Mean): 4.59 -> 3.58Helped
Use the data-driven nearest-neighbor color mapping instead of diagonal WB correction on linearized sRGBImproperly white-balanced images · Extrinsic set (Set 2)MSE (Mean): 385.23 -> 171.09Helped
Use the data-driven nearest-neighbor color mapping instead of diagonal WB correction on linearized sRGBImproperly white-balanced images · Extrinsic set (Set 2)MAE (Mean): 7.22° -> 4.48°Helped
Use the data-driven nearest-neighbor color mapping instead of diagonal WB correction on linearized sRGBImproperly white-balanced images · Extrinsic set (Set 2)ΔE 2000 (Mean): 8.15 -> 5.60Helped

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