Various color difference metrics were developed for characterizing the perceived color difference between individual color patches. Color difference between palettes containing multiple color patches, however, is critically important in product design and computer graphics. This study aimed to investigate how the perceived color difference between a pair of color palettes containing more than a single color patch is affected by the order and number of color patches in the palette. Two reference color sets were generated and each set had four color palettes containing 1, 4, 9, and 16 color patches that were arranged as 1 × 1, 2 × 2, 3 × 3, and 4 × 4 patterns. Human observers scaled the color differences between a color palette of the reference set and a color palette that had revised colors, or revised orders, or a combination of revised colors and orders compared to the reference palette. The calculated color differences between the two palettes were derived using the Minimum Color Difference Model (MICDM) algorithm proposed in a recent work with different color difference metrics, including CIELAB, CMC, CIE94, and DE2000. It was found that the perceived color differences of pairs of individual color patches were significantly larger than those containing multiple patches, when the calculated color differences were the same. The color differences metrics, except for CIE94, had similar performance when characterizing perceived color differences between color palettes.
The difference or distance between two color palettes is a metric of interest in color science. It allows a quantified examination of a perception that formerly could only be described with adjectives. Quantification of these properties is of great importance. The objective of this research is to obtain the dataset for perceptual colour difference between two color palettes and develop color difference metric(s) to correspond well with the perceptual color difference. The psychophysical experiment was carried out using Magnitude Estimation method. Three different color difference metrics, namely Single Color Difference Model (Modell), Mean Color Difference Model (Model 2), and Minimum Color Difference Model (Model 3), respectively, have been proposed and compared. Data analysis include regression analysis, statistical STRESS analysis, and examination of observer variability using coefficient of variance (CT). The results show that the Minimum Color Difference Model (Model 3) outperformed the other two with a coefficient of determination (R-squared) value of 0.603 and an STRESS value of 20.95. In terms of observer variability, the average intra-observer variability is 17.63 while the average inter-observer variability is 53.73.