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Issue No.06 - November/December (2009 vol.15)
pp: 1291-1298
Color vision deficiency (CVD) affects approximately 200 million people worldwide, compromising the ability of these individuals to effectively perform color and visualization-related tasks. This has a significant impact on their private and professional lives. We present a physiologically-based model for simulating color vision. Our model is based on the stage theory of human color vision and is derived from data reported in electrophysiological studies. It is the first model to consistently handle normal color vision, anomalous trichromacy, and dichromacy in a unified way. We have validated the proposed model through an experimentalevaluation involving groups of color vision deficient individuals and normal color vision ones. Our model can provide insights and feedback on how to improve visualization experiences for individuals with CVD. It also provides a framework for testing hypotheses about some aspects of the retinal photoreceptors in color vision deficient individuals.
Models of Color Vision, Color Perception, Simulation of Color Vision Deficiency, Anomalous Trichromacy, Dichromacy.
Gustavo M. Machado, Manuel M. Oliveira, Leandro A. F. Fernandes, "A Physiologically-based Model for Simulation of Color Vision Deficiency", IEEE Transactions on Visualization & Computer Graphics, vol.15, no. 6, pp. 1291-1298, November/December 2009, doi:10.1109/TVCG.2009.113
[1] M. Alpern and T. Wake, Cone pigments in human deutan colour vision defects. Journal of Physiology, 266 (3): 595–612, 1977.
[2] T. T. Berendschot, J. van de Kraats, and D. van Norren, Foveal cone mosaic and visual pigment density in dichromats. Journal of Physiology, 492 .1: 307–314, 1996.
[3] L. Bergman, B. Rogowitz, and L. Treinish, A rule-based tool for assisting colormap selection. In Proc. Visualization '95, pages 118–125, 1995.
[4] H. Brettel, F. Viénot, and J. D. Mollon, Computerized simulation of color appearance for dichromats. J. Opt Soc. Am., 14 (10): 2647–2655, 1997.
[5] J. Carl, R. Ingling, and B. H.-P. Tsou, Orthogonal combination of the three visual channels. Vision Res., 17 (9): 1075–1082, 1977.
[6] C. M. Cicerone and J. L. Nerger, The density of cones in the fovea centralis of the human dichromat. Vision Res., 29: 1587–1595, 1989.
[7] P. DeMarco, J. Pokorny, and V. C. Smith, Full-spectrum cone sensitivity functions for x-chromosome-linked anomalous trichromats. Soc. Am. A, 9 (9): 1465–1476, 1992.
[8] M. D. Fairchild, Color Appearance Models. Addison Wesley, 1997.
[9] D. Farnsworth, The Farnsworth-Munsell 100-hue test for the examination of color discrimination. Munsell Color Company, NY, 1957.
[10] C. H. Graham and Y. Hsia, Studies of color blindness: A unilaterally dichromatic subject. Proc. Natl. Acad. Sci. USA, 45 (1): 96–99, 1959.
[11] C. G. Healey, Choosing effective colours for data visualization. In Proc. of the 7th IEEE Conference on Visualization, pages 263–270, 1996.
[12] S. Ishihara, Tests for colour-blindness. Kanehara Shuppan Co., 1979.
[13] D. B. Judd, Color perceptions of deuteranopic and protanopic observers. J. Opt Soc. Am., 39 (3): 252, 1949.
[14] D. B. Judd, Response functions for types of vision according to the Müller theory. J. Res Natl. Bur. Std., 42 (1): 1–16, January 1949.
[15] D. B. Judd, Fundamental studies of color vision from 1860 to 1960. Proc. Natl. Acad. Sci. USA, 55 (6): 1313–1330, 1966.
[16] S. Kondo, A computer simulation of anomalous color vision. In Y. Ohta editor Color Vision Deficiencies, pages 145–159. Symp. Int. Res. G. on CVD, Kugler & Ghedini, 1990.
[17] G. R. Kuhn, M. M. Oliveira, and L. A. F. Fernandes, An efficient naturalness-preserving image-recoloring method for dichromats. IEEE TVCG, 14 (6): 1747–1754, 2008.
[18] H. Levkowitz and G. T. Herman, Color scales for image data. IEEE CG&A, 12 (1): 72–80, 1992.
[19] D. McIntyre, Colour Blindness: Causes and Effects. Dalton Publ., 2002.
[20] G. W. Meyer and D. P. Greenberg, Color-defective vision and computer graphics displays. IEEE Comput. Graph. Appl., 8 (5): 28–40, 1988.
[21] M. Neitz and J. Neitz, Molecular genetics of color vision and color vision defects. Arch. Ophthalmol., 118 (3): 691–700, 2000.
[22] J. Pokorny and V. C. Smith, Evaluation of single-pigment shift model of anomalous trichromacy. J. Opt Soc. Am., 67 (9): 1196–1209, 1997.
[23] K. Rasche, R. Geist, and J. Westall, Re-coloring images for gamuts of lower dimension. Comput. Graph. Forum, 24 (3): 423–432, 2005.
[24] P. Rheingans, Task-based color scale design. In SPIE-Int. Soc. Opt. Eng., volume 3905, page 3343, 2000.
[25] C. Rigden, The eye of the beholder - designing for colour-blind users. Br Telecomm Eng, 17, 1999.
[26] W. A. H. Rushton, A cone pigment in the protanope. Journal of Physiology, 168 (2): 345–359, September 1963.
[27] L. T. Sharpe, A. Stockman, H. Jägle, and J. Nathans, Color Vision: From Genes to Perception, chapter Opsin genes, cone photopigments, color vision, and color blindness, pages 3–51. Cambridge University Press, 1999.
[28] V. Smith and J. Pokorny, Spectral sensitivity of the foveal cone photopigments between 400 and 500 nm. Vision Res., 15 (2): 161–171, 1975.
[29] J. J. Vos and P. L. Walraven, On the derivation of the foveal receptor primaries. Vision Res., 11 (8): 799–818, 1971.
[30] C. Ware, Color sequences for univariate maps: Theory, experiments and principles. IEEE C&GA, 8 (5): 41–49, 1988.
[31] M. F. Wesner, J. Pokorny, S. K. Shevell, and V. C. Smith, Foveal cone detection statistics in color-normals and dichromats. Vision Res., 31 (6): 1021–1037, 1991.
[32] G. Wyszecki and W. S. Stiles, Color Science: concepts and methods, quantitative data and formulae. John Wiley and Sons, 2nd edition, 2000.
[33] S. Yang, Y. M. Ro, E. K. Wong, and J.-H. Lee, Quantification and standardized description of color vision deficiency caused by anomalous trichromats - Part I: Simulation and measurement. EURASIP Journal on Image and Video Processing, 2008(1), 2008.
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