Chromatic discrimination of natural objects

Journal of Vision

Volumn 8, Issue 1, 2008, Pages 1-19

  Hansen, Thorsten ^a   Giesel, Martin ^a   Gegenfurtner, Karl R ^a  

^a JUSTUS LIEBIG UNIVERSITY   (Germany)

Author keywords

Chromatic discrimination; Chromatic distribution; Chromatic textures; Natural objects; Spatial frequency

Indexed keywords

ARTICLE; COLOR VISION; COLOR VISION TEST; COMPARATIVE STUDY; HUMAN; INSTRUMENTATION; PATTERN RECOGNITION; PERCEPTIVE DISCRIMINATION; PHOTOSTIMULATION; PHYSIOLOGY; REFERENCE VALUE;

COLOR PERCEPTION; COLOR PERCEPTION TESTS; DISCRIMINATION (PSYCHOLOGY); HUMANS; PATTERN RECOGNITION, VISUAL; PHOTIC STIMULATION; REFERENCE VALUES;

EID: 38549091639     PISSN: None     EISSN: 15347362     Source Type: Journal    
DOI: 10.1167/8.1.2     Document Type: Article

References (81)

1. Alder, C. (1981). A Monte Carlo method for the validation of discrimination ellipse data. Journal of the Society of Dyers and Colourists, 97, 514-517.
2. Bergen, J. R., & Adelson, E. H. (1988). Early vision and texture perception. Nature, 333, 363-364.
3. Bergen, J. R., & Landy, M. S. (1991). Computational modeling of visual texture segregation. In M. S. Landy, & J. A. Movshon (Eds.), Computational models of visual processing. Cambridge, MA: MIT Press.
4. Boynton., R. M.. & Kambe, N. (1980). Chromatic difference steps of moderate size measured along theoretically critical axes. Color Research and Application, 5, 13-23,
5. Brown, W. R. (1957). Color discrimination of twelve observers. Journal of the Optical Society of America, 47, 137-143.
6. Brown, W. R., & MacAdam, D. L. (1949). Visual sensitivities to combined chromaticity and luminance differences. Journal of the Optical Society of America, 39, 808-834.
7. Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter. B., Levi, D., et al. (1999). The development of an image/threshold database for designing and testing human vision models. In B. Rogowitz, & T. Pappas (Eds.), Human vision, visual processing, and digital display IV (vol. 3644, pp. 542-551.). Bellingham, WA: SPIE.
8. Carney, T., Tyler, C. W., Watson, A. B., Makous, W., Beutter, B., Chen, C.-C., et al. (2000). ModelFest: Year one results and plans for future years. In B. Rogowitz, & T. Pappas (Eds.), Human vision, visual processing, and digital display V (vol. 3959, pp. 140-151). Bellingham, WA: SPIE,
9. Chen, C.-C., Foley, J. M., & Brainard, D. H. (2000). Detection of chromoluminance patterns on chromoluminance pedestals II: Model. Vision Research, 40, 789-803.
10. Chen, C.-C., & Tyler, C. W. (2000). ModelFest: Imaging the underlying channel structure. In B. Rogowitz, & T. Pappas (Eds.), Human vision, visual processing, and digital display V (vol. 3959, pp. 152-159). Bellingham, WA: SPIE.
11. CIE (1978), Recommendations on uniform color spaces, color-difference equations, psychometric color terms. Supplement No. 2 of CIE Publ. No. 15 (E-1.3.1) 1971, Bureau Central de la CIE, Paris, 1978.
12. CIE (1998). The CIE 1997 Interim Colour Appearance Model (Simple Version), CIECAM97s (Publication 116-198). Paris: Bureau Central de la CIE.
13. CIE (2004). A Colour Appearance Model for Colour Management Systems: CIECAM02 (Publication 159). Paris: Bureau Central de la CIE.
14. Daly. S. (1993). The visible difference predictor: An algorithm for the assessment of image fidelity. In A. B. Watson (Ed.), Digital images and human vision (pp. 179-206). Cambridge, MA: MIT Press.
15. Derrington, A. M., Krauskopf, J., & Lennie, P. (1984). Chromatic mechanisms in lateral geniculate nucleus of macaque. The Journal of Physiology, 357, 241-265.
16. D'Zmura, M., & Knoblauch, K. (1998). Spectral bandwidth for the detection of color. Vision Research, 38, 3117-3128.
17. Fairchild, M. D. (1998). Color appearance models. Reading, MA: Addison-Wesley.
18. Field, D. J. (1987). Relations between the statistics of natural images and the response properties of cortical cells. Journal of the Optical Society of America A, Optics and image science, 4, 2379-2394.
19. Gegenfurtner, K. R., & Kiper, D. C. (1992). Contrast detection in luminance and chromatic noise. Journal of the Optical Society of America A, Optics and image science, 9, 1880-1888.
20. Goda, N., & Fujii, M. (2001). Sensitivity to modulation of color distribution in multicolored textures. Vision Research, 41, 2475-2485.
21. Godlove. I. H. (1952). Near-circular Adams chromaticity diagrams. Journal of the Optical Society of America, 42, 204-212.
22. Halíř R., & Flusser J. (1998). Numerically stable direct least squares fitting of ellipses. In Proceedings of the 6th International Conference in Central Europe on Computer Graphics and Visualization (pp. 125-132). WSCG '98. CZ, Plzeň.
23. Hansen, T., & Gegenfurtner, K. R. (2006). Higher level chromatic mechanisms for image segmentation. Journal of Vision, 6(3):5, 239-259, http://journalofvision.org/6/3/5/, doi:10.1167/6.3.5.
24. Hansen, T., Olkkonen, M., Walter, S., & Gegenfurtner, K. R. (2006). Memory modulates color appearance. Nature Neuroscience, 9, 1367-1368.
25. Hillis, J. M., & Brainard, D. H. (2005). Do common mechanisms of adaptation mediate color discrimination and appearance? Uniform backgrounds. Journal of the Optical Society of America A, Optics, image science, and vision, 22, 2090-2106.
26. Huertas, R.. Melgosa, M., & Oleari, C. (2006). Performance of a color-difference formula based on OSAUCS space using small-medium color differences. Journal of the Optical Society of America A, Optics, image science, and vision, 23, 2077-2084.
27. Judd, D. B. (1951). Report of U. S. secretariat committee on colorimetry and artificial daylight. In Proceedings of the Twelft Session of the CIE, Stockholm. Paris: Bureau Central de la CIE.
28. Kawamoto, K., Inamura, T., & Shioiri, S. (2003). Color discrimination characteristics depending on the background color in the (L, M) plane of a cone space. Optical Review, 10, 391-397.
29. Kiener, S. (1997), On the relationship between two types of effects caused by color adaptation: Changes in color appearance and color discriminability. Journal of Mathematical Psychology, 41, 107-121.
30. Klein, S. A. (1993). Image quality and image compression: A psychophysicist's viewpoint. In A. B. Watson (Ed.), Digital images and human vision (pp. 73-88). Cambridge, MA: MIT Press.
31. Krauskopf, J., & Gegenfurtner, K. (1992). Color discrimination and adaptation. Vision Research, 32, 2165-2175.
32. Krauskopf, J., Williams, D. R., & Heeley, D. W. (1982). Cardinal directions of color space. Vision Research, 22, 1123-1131.
33. Li, A., & Lennie, P. (t997). Mechanisms underlying segmentation of colored textures. Vision Research, 37, 83-97.
34. Loomis, J. M., & Berger, T. (1979). Effects of chromatic adaptation on color discrimination and color appearance. Vision Research, 19, 891-901.
35. Lovell, P. G., Párraga, C. A., Troscianko, T., Ripamonti, C., & Tolhurst, D. J. (2006). Evaluation of a multiscale color model for visual difference prediction. ACM Transactions on Applied Perception, 3, 155-178.
36. Luo, M. R., Cui, G., & Li, C. (2006). Uniform colour spaces based on CIECAM02 colour appearance model. Color Research and Application, 31, 320-330.
37. MacAdam, D. L. (1942). Visual sensitivities to color differences in daylight. Journal of the Optical Society of America, 32, 247-274.
38. MacAdam, D. L. (1944). On the geometry of color space. Journal of the Franklin Institute, 238, 195-210.
39. MacLeod, D. I., & Boynton, R. M. (1979). Chromaticity diagram showing cone excitation by stimuli of equal luminance. Journal of the Optical Society of America, 69, 1183-1186.
40. Miyahara, E, Smith, V. C., & Pokorny, J. (1993). How surround affect chromaticity discrimination. Journal of the Optical Society of America A, Optics and image science, 69, 1183-1186.
41. Moon, P., & Spencer, D. E. (1943). Metric for color space. Journal of the Optical Society of America, 33, 260-269.
42. Moroney, N., Fairchild, M. D., Hunt, R. W. G., Li, C., Luo, M. R., & Newmann. T. (2002). The CIECAM02 Color Appearance Model. In Proceedings of the Tenth Color Imaging Conference: Color Science, Systems and Applications (pp. 23-27).
43. Neumann, D., & Gegenfurtner, K. R. (2006). Image retrieval and perceptual similarity. ACM Transactions on Applied Perception, 3, 31-47.
44. Newhall, S. M., Nickerson D., & Judd D. B. (1943). Final report of the O. S. A. subcommittee on spacing of the Munsell colors. Journal of the Optical Society of America, 33, 385-418.
45. Noorlander,'C., & Koenderink, J. J. (1.983). Spatial and temporal discrimination ellipsoids in color space. Journal of the Optical Society of America, 73, 1533-1543.
46. Poirson, A. B., Wandell, B. A., Varner, D. C., & Brainard, D. H. (1990). Surface characterizations of color thresholds: Journal of the Optical Society of America A, Optics and image science, 7, 783-789.
47. Rinner, O., & Gegenfurtner, K. R. (2000). Time course of chromatic adaptation for color appearance and discrimination. Vision Research, 40, 1813-1826.
48. Sachtler, W. L., & Zaidi, Q. (1992). Chromatic and luminance signals in visual memory. Journal of the Optical Society of America A, Optics and image science, 9, 877-894.
49. Saunderson, J. L., & Milner, B. P. (1944). Further study of omega space. Journal of the Optical Society of America, 34, 167-173.
50. Saunderson, J. L., & Milner, B. I. (1946). Modified chromatic value space. Journal of the Optical Society of America, 36, 36-42.
51. Schrödínger, E. (1920). Grundlinien einer Theorie der Farbenmetrik im Tagessehen. Annalen der Physik, 4, 397-426.
52. Shapiro, A. G., Beere, J. L., & Zaidi, Q. (2001). Time course of adaptation along the RG cardinal axis. Color Research and Application, 26, 43-47.
53. Shapiro, A. G., Beere, J. L., & Zaidi, Q. (2003). Time-course of S-cone system adaptation to simple and complex fields. Vision Research, 43, 1135-1147.
54. Shapiro, A. G., & Zaidi, Q. (1992). The effect of prolonged temporal modulation on the differential response of color mechanisms. Vision Research, 32, 2065-2075.
55. Smith, V. C., & Pokorny, J. (1996). Color contrast under controlled chromatic adaptation reveals opponent rectification. Vision Research, 36, 3087-3105.
56. Smith, V. C., Pokorny, J., & Sun, H. (2000). Chromatic contrast discrimination: Data and prediction for stimuli varying in L and M cone excitation. Color Research and Application, 25, 105-115.
57. Stiles, W. S. (1959). Colour vision: The approach through increment-threshold sensitivity. Proceedings of the National Academy of Sciences of the United States of America, 45, 100-114.
58. Sumner, P., & Mollon, J. D. (2000). Chromaticity as a signal of ripeness in fruits taken by primates. Journal of Experimental Biology, 203, 1997-2000.
59. te Pas, S. F.. &, Koenderink, J. J. (2004). Visual discrimination of spectral distributions. Perception, 33, 1483-1497.
60. von Helmholtz, H. L. F. (1867). Handbuch der physiologischen Optik. Hamburg und Leipzig: Voss.
61. Walls, G. L. (1942). The vertebrate eye and its adaptive radiation. Bloomfield Hills, MI: The Cranbrook Institute of Science.
62. Watson. A. B. (2000). Visual. detection of spatial contrast patterns: Evaluation of five simple models. Optics Express, 6, 12-33.
63. Watson. A. B., & Ahumada, A. J., Jr. (1989). A hexagonal orthogonal-oriented pyramid as a model of images representation in visual cortex. IEEE Transactions on Biomedical Engineering, 36, 97-106.
64. Watson, A. B., & Ahumada, A. J., Jr. (2005). A standard model for foveal detection of spatial contrast. Journal of Vision, 5(9):6, 717-740, http://journalofvision.org/5/9/6/, doi:10.1167/5.9.6.
65. Watson. A. B., & Ramirez, C. (1999). A standard observer for spatial vision based on ModelFest dataset. Optical Society of America Annual Meeting. Digest of Technical Papers, SuC6.
66. Webstér, M. A., & Mollon, J. D. (1991). Changes in colour appearance following post-receptoral adaptation. Nature, 349, 235-238.
67. Webster, M. A., & Mollon, J. D. (1994). The influence of contrast adaptation on color appearance. Vision Research, 34, 1993-2020.
68. Webster, M. A., & Mollon, J. D. (1997). Adaptation and the color statistics of natural images. Vision Research, 37, 3283-3298.
69. Wichmann, F. A., & Hill, N. J. (2001). The psychometric function: 1. Fitting, sampling and goodness of fit. Perception & Psychophysics, 63, 1293-1313.
70. Wilson, H. R., & Regan, D. (1984). Spatial-frequency adaptation and grating discrimination: Predictions of a line-element model. Journal of the Optical Society of America A, Optics and image science, 1, 1091-1096.
71. Wright, W. D. (1941). The sensitivity of the eye to small colour differences. Proceedings of the Physical Society of London, 53, 93-112.
72. Wyszecki, G. (1963). Proposal for a new colour-difference formula. Journal of the Optical Society of America, 53, 1318-1319.
73. Wyszecki, G., & Fielder, G. H. (1971a). Color difference matches. Journal of the Optical Society of America, 61, 1501-1513.
74. Wyszecki, G., & Fielder, G. H. (1971b). New color-matching ellipses. Journal of the Optical Society of America, 61, 1113-1152.
75. Wyszecki, G., & Stiles, W. S. (1982). Color science. Concepts and methods, quantitative data and formulae (2nd ed.). New York: Wiley.
76. Xu, H., Yaguchi, H., & Shioiri, S. (2002). Correlation between visual and colorimetric scales ranging from threshold to large color difference. Color Research and Application, 27, 349-359.
77. Zaidi, Q., Shapiro, A., & Hood, D. (1992). The effect of adaptation on the differential sensitivity of the S-cone color system. Vision Research, 32, 1297-1318.
78. Zaidi. Q., Spehar, B., & DeBonet, J. (1998). Adaptation to textured chromatic fields. Journal of the Optical Society of America A, Optics, image science, and vision, 15, 23-32.
79. Zete, A. J., Smith, V. C., & Pokorny, J. (2006). Spatial and temporal chromatic contrast: Effects on chromatic discrimination for stimuli varying in L- and M-cone excitation. Visual Neuroscience, 23, 495-501.
80. Zhang, X. M., & Wandell, B. A. (1996). A spatial extension to CIELAB for digital color image reproduction. Proceedings of the Society for Information Display, 96, 731-734.
81. Zhang, X. M., & Wandell, B. A. (1998). Color image fidelity metrics evaluated using image distortion maps. Signal Processing, 70, 201-214.