CIEDE2000 Color Difference Formula Research Articles

Study of the Variation between CIELAB .DELTA.E* and CIEDE2000 Color-differences of Resin Composites

This study sought to assess the significance of the corrections introduced in the new CIEDE2000 color difference formula with respect to deltaE*ab. The purpose of which was to provide sounder knowledge, and hence more informed decision-making, about applying this new formula to dental resin composites. With two different hybrid composites, color differences were calculated between unpolymerized and polymerized resin composites, between polymerized resin composites of different thicknesses (1 and 2 mm), and between polymerized resin composites cured with halogen and LED light curing units (LCUs). The two formulas differed significantly, with VAB(E) (equal size) values higher than the inter-observer variability (VAB (E)=11%) and VAB(O) (original size) values greater than 25% for each of the data sets analyzed. Results obtained in this study agreed with and thus supported the recent recommendation of the Commission Internationale de l'Eclairage (CIE), whereby the new CIEDE2000 formula should be used to evaluate color differences of resin composites.

Influence of random-dot textures on perception of suprathreshold color differences

We have analyzed the way in which simulated textures made of random dots influence visual suprathreshold color tolerances. We considered 32 textures created by a systematic variation of the following variables: size, number, and color of the dots. Each texture was mapped on the five centers recommended by the International Commission on Illumination (CIE) in 1978 [Color Res. Appl.3, 149 (1978)]. A panel of five experienced observers determined the experimental tolerances using a CRT color monitor by the method of adjustment. At our observation distance, neither small differences in dot size (1 or 4 pixels) nor sparse number of dots (less than 20% of the surface of the sample) changed the tolerances found for homogeneous samples. For the textures that led to statistically significant differences with respect to homogeneous samples, the parametric factors of CIEDE2000 and CIE94 color-difference formulas were fitted. These simulated textures consistently reduced the color difference perceived in a pair or, equivalently, increased the tolerances, mainly (but not only) lightness tolerance. The results demonstrate that it is not simple to provide a unique set of parametric factors for all the potential textures.

Computational Surface Models for Chromaticity Differences

In this study the purpose was to develop a computational surface model, which gives an equal computed chromaticity difference for equal perceived chromaticity difference in every part of the color space. The computational surface model assess chromaticity differences based on the surfaces defined by an ellipse data set and the two chromaticity points whose chromaticity difference is to be calculated. The distances along the surfaces are calculated by a method based on the Weighted Distance Transform On Curved Space (WDTOCS). The ellipse data sets are the MacAdam ellipses in the CIE 1931 (x,y)-chromaticity diagram and the ellipses which are fitted from the visual color difference measurements used in deriving the CIE DE2000 color difference formula in the CIELAB color space. In general the ellipse data set can be any set of planar chromaticity ellipses. The chromaticity differences calculated along the surfaces correct the planar chromaticity values, thus these differences match better with perceived chromaticity differences. The experiments are made in the vicinity of the chromaticity difference ellipses and the results are contrasted with CIE DE2000.

Relative significance of the terms in the CIEDE2000 and CIE94 color-difference formulas

CIELAB-based color-difference formulas are used to improve the prediction of visually perceived color differences through the introduction of various corrections to CIELAB. In our study we analyze the relative importance of these corrections. From the combined dataset employed for the development of CIEDE2000, we found that the improvement of CIE94 over CIELAB was considerably greater than that of CIEDE2000 over CIE94. Chroma-difference correction was the most important correction in both CIE94 and CIEDE2000. With an arbitrary value of 100 assigned to this correction, the score of the hue-difference correction in CIE94 was 21, and the scores of the four remaining corrections in CIEDE2000 were as follows: hue difference, 29; rotation term, 8; lightness difference, 8; and gray correction, 6. At 95% confidence level each of the corrections introduced in CIEDE2000 or CIE94 was statistically significant for the whole combined dataset, in agreement with the results reported by CIE TC 1-47 and 1-29. For the combined dataset, the differences between CMC and CIEDE2000 were found to be statistically significant at 95% confidence level, but the differences between CMC and CIE94 were not. From subsets of the combined dataset it was concluded that further analyses of the lightness-difference and gray corrections proposed by CIEDE2000 would be desirable, using new experimental data.

The CIEDE2000 color-difference formula: Implementation notes, supplementary test data, and mathematical observations

This article and the associated data and programs provided with it are intended to assist color engineers and scientists in correctly implementing the recently developed CIEDE2000 color-difference formula. We indicate several potential implementation errors that are not uncovered in tests performed using the original sample data published with the standard. A supplemental set of data is provided for comprehensive testing of implementations. The test data, Microsoft Excel spreadsheets, and MATLAB scripts for evaluating the CIEDE2000 color difference are made available at the first author's website. Finally, we also point out small mathematical discontinuities in the formula. © 2004 Wiley Periodicals, Inc. Col Res Appl, 30, 21–30, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20070

On the relationship between tilt of a*b* tolerance ellipses in blue region and tritanopic confusion lines

AbstractThere is reasonable agreement between the orientation of the major axes of the a*b* tolerance ellipses in the blue region and the slope of the tritanopic confusion lines passing through their centers. This agreement includes some experimental facts such as the approximate constant orientation of the ellipses when the luminance of the center changes and the clockwise rotation of the major axis of the ellipses when the luminous source D65 is replaced by A. However, the tilts predicted by the tritanopic lines do not follow the pattern proposed by the CIEDE2000 color‐difference formula; in particular, for the blue‐green centers with hue angles lower than 255°, the high tilts predicted by the tritanopic lines are quite different. From 132 ellipses previously reported, we found that the orientations of the 17 ellipses in the blue region (255° < h < 320°) were similarly predicted by both CIEDE2000 and the tritanopic confusion lines (average error of 12.2° in absolute value). © 2002 Wiley Periodicals, Inc. Col Res Appl, 27, 180–184, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.10053