RELIABILITY ESTIMATION FOR SCREEN REPRODUCTION OF SATURATED PIGMENTS

L. . Сherevan, Тозик В. Т.


Read the full article 

Abstract

The paper deals with the ability of modern display monitors to reproduce full color range of classical oil paintings. The models of the standard color gamuts of modern monitors are represented by visualization in CIELab color coordinate system. Pure mineral pigments are proved to be more saturated than oil colors. Therefore, reproduction ability of pure saturated pigments ensures the full range reproduction of oil colors. 75 color coordinates of pure pigments are obtained by means of the spectrophotometry method. The measured coordinates displacement is shown as compared with the color gamuts of standard monitors. The quantitative method of reliability estimation for the reproducing of full color ranges of classical oil paintings is developed. The method consists of color differences calculating for out-of-gamut colors (measuring that of the reference coordinate against the closest one inside the gamut) and comparing the results with the standard threshold color difference. It is proved that sRGB monitor does not represent effectively the full color range of classical oil paintings, and AdobeRGB monitor reproduces satisfactorily the full range of colors (with the difference below the threshold of human perception). Developed quantitative method can be applied for any kind of monitor estimation.


Keywords: monitors, color, color coordinates, CIE, CIEXYZ, CIELab, screen reproduction

References
 1. Saunders D., Hamber А. From Pigments to Pixels: Measurement and Display of the Colour Gamut of Paintings // Proc. of SPIE. 1990. V. 1250. Р. 90–102.
2. Wandell B., Silverstein D. Digital Color Reproduction // The Science of Color / Ed. S. Shevell. 2nd ed. Optical Society of America, 2003. P. 281–316.
3. McDermott K.C., Webster M.A. Uniform color spaces and natural image statistics // J. Opt. Soc. Am. A. 2012. V. 29. N 2. P. A182–A187.
4. Fairchild M.D. Color Appearance Models. 2nd ed. John Wiley & Sons, Ltd, 2005. 408 р.
5. Tominaga S., Tanaka N. Spectral image acquisition, analysis, and rendering for art paintings // J. Electronic Imaging. 2008. V. 17. N. 4. P. 6–13.
6. Акмаров К.А., Белов Н.П., Смирнов Ю.Ю., Шерстобитова А.С., Щербакова Е.Ю., Яськов А.Д. Лабо- раторный спектрофотометр для видимой области спектра // Научно-технический вестник информаци- онных технологий, механики и оптики. 2013. № 5 (87). С. 39–44.
7. ГОСТ 16873-92 (ИСО 787/1-82). Пигменты и наполнители неорганические. Методы определения цве- та и белизны. Введ. 01.07.93. М.: Изд-во стандартов, 1992. 10 с.
8. Юстова Е.Н. Цветовые измерения (Колориметрия). СПб: Изд-во СПбГУ, 2000. 397 с.
9. Ohta N., Robertson A. Colorimatry: Fundamentals and Applications. John Wiley & Sons, Inc., 2005. 350 p.
10. Hunt R.W.G. The Reproduction of Colour. 6th ed. John Wiley & Sons, Ltd, 2004. 724 р.
11. Gijsenij A., Gevers T., Weijer J. Generalized Gamut Mapping Using Image Derivative Structures for Color Constancy // Int. J. Computer Vision. 2010. V. 86. N 2. P. 127–139.
12. Lindbloom B.J. Useful Color Information, Studies and Files. 2001–2013 [Электронный ресурс]. Режим доступа: http://www.brucelindbloom.com/, свободный. Яз. англ. (дата обращения 26.10.2013).
13. Robertson Ph., Schönhut J. Color in Computer Graphics // IEEE Computer Graphics and Applications. 1999. V. 19. N 4. P. 18–19.
14. Лентовский А.М. Технология живописных материалов. Л. –М.: Искусство, 1949. 220 с.
15. Филатов В.В. Реставрация настенной масляной живописи. М.: Изобразительное искусство, 1995. 248 с.
16. ГОСТ 7086-75. Краски печатные. Методы определения прозрачности. Введ. 01.01.77. М.: Изд-во стандартов, 2003. 7 с.
17. Sharma G., Wu W., Dalal E.N. The CIEDE2000 Color-Difference Formula: Implementation Notes, Supplementary Test Data, and Mathematical Observations // Submitted to Color Research and Application. 2004. V. 16. N 3. P. 217–218.
18. ISO 12647-7:2007(E). Graphic technology – Process control for the production of half-tone colour separations, proof and production prints. Part 7: Proofing processes working directly from digital data. 20 р.
19. Hansen T., Olkkonen M., Walter S., Gegenfurtner K. Memory Modulates Color Appearance // Nature Neuroscience. 2006. V. 9. N 11. P. 1367–1368.
20. Lau C., Heidrich W., Mantiuk R. Cluster-based color space optimizations // IEEE International Conference on Computer Vision (ICCV). 2011. P. 1172–1179.
Copyright 2001-2017 ©
Scientific and Technical Journal
of Information Technologies, Mechanics and Optics.
All rights reserved.

Яндекс.Метрика