A comprehensive test of colour‐difference formulae and uniform colour spaces using available visual datasets. Issue 3 (1st February 2023) - Luo, Ming Ronnier
Abstract: The paper describes a comprehensive test to evaluate the performance of current colour‐difference models using available experimental datasets. In total, 28 individual datasets were accumulated to test 17 colour‐difference formulae, 13 of them based on Uniform Colour Spaces (UCSs) in terms of the Standardized Residual Sum of Squares ( STRESS ) measure. The 28 datasets were divided into three groups: Large Colour‐Difference data (LCD), Small Colour‐Difference data for surface colours (SCDs), and Small Colour Difference data for display colours (SCDd). For each colour model, four versions were tested: the original model, and that including k L ‐, Gamma‐ and k L /Gamma, which are the lightness parametric factor, the colour‐difference exponent factor, and the combination of both, respectively, optimized to fit particular dataset(s). The statistical F ‐test was applied to test the difference between each pair of models. Furthermore, parametric effects between the large/small colour‐difference magnitudes, and between surface/display colours were investigated. The results showed that CAM16‐UCS significantly outperformed the other models for all groups. It accurately predicted all types of data and should be proposed for colour‐difference evaluation across all industries. Abstract : Relative average scores achieved by each of the 17 colour‐difference formulas for: (A) original (V1) and (B) k L /Gamma (V4) models for each of three groups (SCDs, SCDd and LCD), assuming scores of 10 / 7.5 / 5 / 2.5 / 0 when a formula is significantly better / insignificantly better / identical / insignificantly worse / significantly worse than another one, respectively, from F ‐test based on the STRESS index. 11