Performance of select color-difference formulas in the blue region

Area of Science:

• Color Science
• Perceptual Colorimetry
• Textile Coloration

Background:

• Accurate assessment of small suprathreshold color differences is crucial in industries like textiles.
• Existing color difference formulas, primarily based on the CIELAB color space, have limitations in predicting perceptual uniformity, especially in the blue region.
• Development of more perceptually uniform color spaces is essential for improved color difference prediction.

Purpose of the Study:

• To evaluate the performance of various color difference formulas for small suprathreshold color differences in the blue region.
• To compare CIELAB-based models against formulas derived from more uniform color spaces using visual assessment data.
• To validate formula performance using a newly developed high-chroma blue dataset (NCSU-B2) and existing datasets.

Main Methods:

• Developed the NCSU-B2 dataset comprising 65 textile substrates with a mean ΔE(ab)* of 2.72.
• Conducted visual assessments of color differences by 26 subjects across three trials.
• Analyzed formula performance using the standardized residual sum of squares (STRESS) index against visual data and other blue datasets.

Main Results:

• Formulas based on more recent uniform color spaces demonstrated superior agreement with perceptual data compared to CIELAB-based models.
• The NCSU-B2 dataset provided a robust benchmark for evaluating color difference formulas in the high-chroma blue region.
• Specific formulas like CAM02-SCD, CAM02-UCS, DIN99d, OSA-GP, and OSA-Eu showed better performance than CIELAB, CIE94, and CIEDE2000.

Conclusions:

• More recent uniform color space models offer improved accuracy in predicting perceived color differences for blue shades.
• The findings suggest a shift towards advanced color models for more reliable color difference assessment in practical applications.
• This research contributes to the refinement of color difference evaluation, particularly for challenging blue color spaces.