Jueqin Qiu, Haisong Xu*, Peng Xu Comparison of Object-Color and Illuminant Metamer Mismatching for Digital Image Color Correction State Key Laboratory of Modern Optical Instrumentation College of Optical Science and Engineering Zhejiang University, China

BACKGROUND | 1

= dλ Metamerism ! Background × × Metamer mismatching is a phenomenon that two object colors, which are colorimetrically indistinguishable under one lighting and viewing condition, become distinguishable under another one. Metamerism !

Background Raw Data After White-balancing Displayable Output

Background Color correction transforms the images to the appearance that captured under a reference illuminant, like D65 Usually completed by linear transformations such as a 3×3 matrix Color correction can possibly enlarge the metamer mismatching Raw Data After White-balancing Displayable Output

METHODS | 2

Methods Object-color Metamer Mismatching 𝜆 Hyper-spectral image (HSI)

Methods Object-color Metamer Mismatching Illuminant A D65 D75 TL84 CWF

Methods 106 hyper-spectral images (HSIs) in total Object-color Metamer Mismatching 106 hyper-spectral images (HSIs) in total Cover most of image categories in daily life: Plants, Human skins, Outdoor scenes, Printing materials, Artifact, etc. For each test hyper-spectral image, 8 test illuminants were repeated and then averaged

Methods Object-color Metamer Mismatching Reconstruction of the color corrected images as well as the object-color metamer mismatching image

printing materials and Methods Object-color Metamer Mismatching Database name Content HSI number Foster plants, architectures and paper products 19 Yasuma Miscellaneous 32 UEF skins and artefacts 12 Skauli facial skins, plants and architectures 33 Moan 9 Hordley printing materials and Packages 21 Parraga Plants 27 Eckhard outdoor scenes and Architectures 14 Spectral Reflectance Database From 8 online databases 7,326,497 samples in total 100% sRGB gamut Duplicates and outliers have been removed

Methods Illuminant Metamer Mismatching Each test illuminant has 2 metamers: daylight series (daylight spectra by Judd) 4-channel LED series (NIST-CQS by Ohno and Davis) F2 (Cool White Fluorescent) 4-ch LED metamer: same chromaticity coordinate Daylight metamer: same correlated color temperature (CCT) but different chromaticity coordinate

Methods Illuminant Metamer Mismatching Each test illuminant has 2 metamers: daylight series (daylight spectra by Judd) 4-channel LED series (NIST-CQS by Ohno and Davis) 4-ch LED metamer: same chromaticity coordinate Daylight metamer: same correlated color temperature (CCT) but different chromaticity coordinate 8 test illuminants in total were investigated: CIE illuminant A, D50, D100, CWF, F8, TL84, D50 LED simulator, and iPhone Flash

RESULTS | 3

Results Ground Truth D65 Cool White Fluorescent Object-color Metamer Mismatching (50%) Object-color Metamer Mismatching (95%) Illuminant Metamer Mismatch (Daylight) Illuminant Metamer Mismatch (4-LED) Color Corrected

Results Full-reference Image Quality Assessment Metric: Directional Statistics based Color Similarity Index (DSCSI)† † Dohyoung Lee et. al., Towards a Full-Reference Quality Assessment for Color Images Using Directional Statistics, IEEE Transactions on Image Processing, 24 (11), Nov, 2015.

Results DSCSI Scores 0.9933 0.9803 0.9508 0.8320 0.9084 Ground Truth Cool White Fluorescent Object-color Metamer Mismatching (50%) Object-color Metamer Mismatching (95%) Illuminant Metamer Mismatch (Daylight) Illuminant Metamer Mismatch (4-LED) Color Corrected 0.9933 0.9803 0.9508 0.8320 0.9084 DSCSI Scores

Results Pooling 106 hyper-spectral images and 8 test illuminants together: Median Quantiles Min & Max

Conclusions Object-color metamer mismatching is tolerable for digital image color correction Illuminant metamer mismatching is more severe to degrade the fidelity of color reproduction Detecting the spectral information of the captured scene is the only way to solve the metamer mismatching Acquisition of the spectral power distribution (SPD) of the light source is much easier than acquiring a hyper-spectral image

Thanks for Your Attention! Jueqin Qiu, Haisong Xu*, Peng Xu Thanks for Your Attention!