Opponent process

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Opponent colors based on experiment. Deuteranopes see little difference between the two colors in the central column.
Diagram of the opponent process

The color opponent process is a color theory that states that the human visual system interprets information about color by processing signals from cones and rods in an antagonistic manner. The three types of cones (L for long, M for medium and S for short) have some overlap in the wavelengths of light to which they respond, so it is more efficient for the visual system to record differences between the responses of cones, rather than each type of cone's individual response. The opponent color theory suggests that there are three opponent channels: red versus green, blue versus yellow, and black versus white (the last type is achromatic and detects light-dark variation, or luminance).[1] Responses to one color of an opponent channel are antagonistic to those to the other color. That is, opposite opponent colors are never perceived together – there is no "greenish red" or "yellowish blue".

While the trichromatic theory defines the way the retina of the eye allows the visual system to detect color with three types of cones, the opponent process theory accounts for mechanisms that receive and process information from cones. Though the trichromatic and opponent processes theories were initially thought to be at odds, it later came to be understood that the mechanisms responsible for the opponent process receive signals from the three types of cones and process them at a more complex level.[2]

Besides the cones, which detect light entering the eye, the biological basis of the opponent theory involves two other types of cells: bipolar cells, and ganglion cells. Information from the cones is passed to the bipolar cells in the retina, which may be the cells in the opponent process that transform the information from cones. The information is then passed to ganglion cells, of which there are two major classes: magnocellular, or large-cell layers, and parvocellular, or small-cell layers. Parvocellular cells, or P cells, handle the majority of information about color, and fall into two groups: one that processes information about differences between firing of L and M cones, and one that processes differences between S cones and a combined signal from both L and M cones. The first subtype of cells are responsible for processing red–green differences, and the second process blue–yellow differences. P cells also transmit information about intensity of light (how much of it there is) due to their receptive fields.[citation needed]


Johann Wolfgang von Goethe first studied the physiological effect of opposed colors in his Theory of Colours in 1810.[3] Goethe arranged his color wheel symmetrically "for the colours diametrically opposed to each other in this diagram are those which reciprocally evoke each other in the eye. Thus, yellow demands purple; orange, blue; red, green; and vice versa: Thus again all intermediate gradations reciprocally evoke each other."[4][5]

Ewald Hering proposed opponent color theory in 1892.[6] He thought that the colors red, yellow, green, and blue are special in that any other color can be described as a mix of them, and that they exist in opposite pairs. That is, either red or green is perceived and never greenish-red: Even though yellow is a mixture of red and green in the RGB color theory, the eye does not perceive it as such. In 1957, Leo Hurvich and Dorothea Jameson provided quantitative data for Hering's color-opponent theory. Their method was called hue cancellation. Hue cancellation experiments start with a color (e.g. yellow) and attempt to determine how much of the opponent color (e.g. blue) of one of the starting color's components must be added to eliminate any hint of that component from the starting color.[7][8]

The opponent color theory can be applied to computer vision and implemented as the Gaussian color model[9] and the natural-vision-processing model.[10][11][12]

Others have applied the idea of opposing stimulations beyond visual systems, described in the article on opponent-process theory. In 1967, Rod Grigg extended the concept to reflect a wide range of opponent processes in biological systems.[13] In 1970, Solomon & Corbit expanded Hurvich & Jameson's general neurological opponent process model to explain emotion, drug addiction, and work motivation.[14][15]

Complementary-color afterimages[edit]

If someone stares at a red square for forty seconds, and then immediately looks at a white sheet of paper, they often perceive a cyan square on the blank sheet. This complementary color afterimage is more easily explained by the trichromatic color theory than the traditional RYB color theory; in the opponent-process theory, fatigue of pathways promoting red produce the illusion of a cyan square.[16]

Combinations of opponent colors[edit]

See also[edit]


  1. ^ Michael Foster (1891). A Text-book of physiology. Lea Bros. & Co. p. 921. Archived from the original on 2017-01-18.
  2. ^ Kandel ER, Schwartz JH and Jessell TM, 2000. Principles of Neural Science, 4th ed., McGraw–Hill, New York. pp. 577–80.
  3. ^ "Goethe's Color Theory". Vision science and the emergence of modern art. Archived from the original on 2008-09-16.
  4. ^ Goethe, Johann (1810). Theory of Colours, paragraph #50.
  5. ^ "Goethe on Colours". The Art-Union. 2 (18): 107. July 15, 1840. Archived from the original on December 21, 2017.
  6. ^ Hering E, 1964. Outlines of a Theory of the Light Sense. Cambridge, Mass: Harvard University Press.
  7. ^ Hurvich, Leo M.; Jameson, Dorothea (November 1957). "An opponent-process theory of color vision". Psychological Review. 64 (6, Part I): 384–404. doi:10.1037/h0041403. PMID 13505974.
  8. ^ Wolfe, Kluender, & Levi, (2009)
  9. ^ Geusebroek, J.-M.; van den Boomgaard, R.; Smeulders, A.W.M.; Geerts, H. (December 2001). "Color invariance". Pattern Analysis and Machine Intelligence, IEEE Transactions on. 23 (12): 1338–1350. doi:10.1109/34.977559.
  10. ^ Barghout, Lauren. (2014). "Visual taxometric approach to image segmentation using fuzzy-spatial taxon cut yields contextually relevant regions". Information Processing and Management of Uncertainty in Knowledge-Based Systems. Springer International Publishing.
  11. ^ Barghout, Lauren, & Lee, Lawrence. (2004-03-25). Perceptual information processing system. Patent US20040059754.
  12. ^ Barghout, Lauren. (2014). Vision: Global Perceptual Context Changes Local Contrast Processing, Updated to include computer vision techniques. Scholars' Press, (21 February 2014).
  13. ^ Grigg, E. R. N. (1967). Biologic Relativity. Chicago: Amaranth Books.
  14. ^ Solomon, R. L.; Corbit, J. D. (1973). "An Opponent-process theory of motivation: II. Cigarette addiction". Journal of Abnormal Psychology. 81 (2): 158–171. doi:10.1037/h0034534.
  15. ^ Solomon, R. L.; Corbit, J. D. (1974). "An Opponent-process theory of motivation: I. Temporal dynamics of affect". Psychological Review. 81 (2): 119–145. doi:10.1037/h0036128.
  16. ^ Griggs, R. A. (2009). "Sensation and perception". Psychology: A Concise Introduction (2 ed.). Worth Publishers. p. 92. ISBN 978-1-4292-0082-0. OCLC 213815202. color information is processed at the post-receptor cell level (by bipolar, ganglion, thalamic, and cortical cells) according to the opponent-process theory.

Further reading[edit]

  • Baccus, S. A. (2007). "Timing and computation in inner retinal circuitry". Annual Review of Physiology. 69: 271–90. doi:10.1146/annurev.physiol.69.120205.124451.
  • Masland, R. H. (2001). "Neuronal diversity in the retina". Current Opinion in Neurobiology. 11 (4): 431–6. doi:10.1016/S0959-4388(00)00230-0.
  • Masland, R. H. (2001). "The fundamental plan of the retina". Nature Neuroscience. 4 (9): 877–86. doi:10.1038/nn0901-877.
  • Sowden, P. T.; Schyns, P. G. (2006). "Channel surfing in the visual brain". Trends in Cognitive Sciences. 10 (12): 538–45. doi:10.1016/j.tics.2006.10.007.
  • Wässle, H. (2004). "Parallel processing in the mammalian retina". Nature Reviews Neuroscience. 5 (10): 747–57. doi:10.1038/nrn1497.