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The CIEDE2000 color‐difference formula: Implementation notes, supplementary test data, and mathematical observations
Sharma, Gaurav; Wu, Wencheng; Dalal, Edul N.
Color research and application,
February 2005, Letnik:
30, Številka:
1
Journal Article
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
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The effect of gloss on color
Dalal, Edul N.; Natale-Hoffman, Kristen M.
Color research and application,
October 1999, Letnik:
24, Številka:
5
Journal Article
A model was developed for the effect of gloss on reflected color, taking the measurement geometry of the color measuring device into account. It considers the total front surface reflectance of a ...
given sample to be independent of gloss and determined only by its refractive index and the angle of the incident beam. Although the total front surface reflectance is fixed, its specular component increases (and the diffuse component decreases) with increasing sample gloss. Therefore, the diffuse reflectance factor measured by a spectrophotometer decreases with sample gloss. In this article, a defined curve was fitted to the measured reflectance factor of black xerographic print samples having a range of gloss values for the 0/45 and diffuse spectrophotometer geometries, and this curve was used to predict the CIELAB color values for samples of the other colors at various gloss levels. The predicted color was compared to the measured color for cyan, magenta, yellow, red, green, and blue images that spanned a wide range of gloss. The RMS color error between the predicted and measured color of all of these images was found to be about 3 CIELAB ΔE* units. © 1999 John Wiley & Sons, Inc. Col Res Appl, 24, 369–376, 1999
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Color printer characterization adjustment for different substrates
Shaw, Mark; Sharma, Gaurav; Bala, Raja ...
Color research and application,
December 2003, Letnik:
28, Številka:
6
Journal Article
The use of multiple substrates in color printers requires color characterization for each of the individual substrates. A full re‐characterization for each substrate is measurement and labor ...
intensive. In this article, a variety of methods are proposed and evaluated for determining the color characterization for a new substrate based on a complete characterization on a reference substrate and a small number of additional measurements for the new substrate. This saves significant time and effort in comparison to the traditional method of repeating the color characterization for each new substrate. The methods developed and tested include model‐based approaches based on Beer's law, Kubelka‐Munk theory, and Neugebauer equations; and an empirical technique based on principal component analysis. Results indicate that the model based techniques offer only a small improvement over direct use of the reference characterization, whereas, the empirical technique offers a more significant improvement with as few as 26 measurements on the new substrate. © 2003 Wiley Periodicals, Inc. Col Res Appl, 28, 454–467, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.10198
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