COLOR INDUCTION AND ADAPTATION

examples of combinations of simultaneous lightness and chromatic contrasts. The small squares on the top of the figure are printed with the same pigments and are thus physically the same as those imbedded in the blue and yellow stripes. The color shifts of the latter are enhanced even more if one tilts the book or views the figure at a greater distance, demonstrating that relative size contributes significantly to the effect. These phenomena are poorly understood, and we shall offer no explanation here.

Colored shadows are much discussed phenomena caused by color induction. You can see them in a viewing condition like that of Figure 5.38. An opaque object is

Screen

ω

Filter

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Figure 5.38 Colored shadows. When a blue and a white light illuminate the same object, the object casts two shadows on the wall. The shadow that is illuminated by the blue light looks blue, as expected, but the one that is illuminated by the white light appears yellow instead of white. The additive color mixture in the surround is nearly white. Other colored lights will also produce a contrast color in the shadow (red light will give a greenish shadow, and green light a reddish shadow, etc.). This surprising contrast effect will be reproduced in a color photograph of the scene. (See also color plate section.)

illuminated by two light sources, one emitting white light and the other chromatic light (bluish in the example). The object casts two shadows on an opposing screen. Either shadow will be illuminated by the other source. The shadow that is illuminated by the blue light looks bluish as expected, whereas the shadow that is illuminated by white light does not look white, but yellow. If the color-inducing light changes from blue to purple, the unchanged white shadow now turns greenish. In some cases, when the color surrounding the shadows is so unsaturated that it can be mistaken for being white, the chromatic shadow effect is still present and surprisingly strong.

It is easy to be convinced that the physically unchanged shadow – the one that is mostly affected by simultaneous contrast and induction – is reflecting the same light in all cases when the color of the chromatic light changes. One can, for instance, isolate the shadow by looking at it through a black tube. If someone changes the color of the chromatic light while you are looking through the tube, you do not to see any

change at all in the achromatic shadow. This can be confirmed by physical color measurements. Consequently, the phenomenon is not physical, meaning that there is no direct physical correlate in the shadow itself that would indicate a change in its colored appearance. The correlate lies in the surround inducing a contrast color into the shadow.

The various forms of simultaneous contrast and induction effects in vision have often been regarded as failures of the visual system to adjust to the actual stimulus and lighting conditions. Von Helmholtz’s psychological interpretation of these phenomena as optical illusions or errors of judgement has strengthened this view. The physiological explanations of Hering and Mach on the other hand, relied less on cognitive, top-down processes than von Helmoltz’s ‘unconscious judgement’. They pointed to induction as a normal neural function, and they regarded the mutual interaction of adjacent areas in the visual field as most important for the enhancement of small physical differences. Since color induction effects appear strong close to threshold contrast (Valberg and Seim, 1983), this may be taken as a confirmation of the latter view.

After one has become aware of the existence and the importance of the many contrast and induction phenomena, one tends to find them everywhere. Indeed, under normal viewing conditions, they are so pronounced that one may well ask if normal vision would be possible without them.

Induced colors

Induced colors are obviously related to a normal neural activity of the visual system, and their dependency on spatial and chromatic parameters provides information about the functioning of the system. For instance, how does an induced color depend on the inducing stimulus? In older literature it was believed that these two colors are complementary, but accurate measurements have revealed that this is correct only for rather unsaturated inducing stimuli. For inducing stimuli that are strongly chromatic, the induced colors deviate more from complementarity the more saturated they become. This is shown in the (x,y)-diagram in Figure 5.39 for an experimental situation as in Figure 5.40. A solid curve in Figure 5.39 shows how the induced color (that was matched by a separate comparison field viewed by the other eye) changes in chromaticity when the inducing color increases in purity (as shown by the two arrows in opposite directions from the white point W). The inducing surround colors are indicated by short dashed line segments ending at a ‘þ’ symbol. One sees that the induced colors follow a curve even though the inducing stimuli are all situated on a straight line of constant dominant wavelength (forming a tangent to the induced hue loci at the white point W). It is worth noting that the curved lines resemble the loci of constant hues in Figure 5.28 (Valberg, 1974; Valberg and Seim, 1983).

The induction process seems to be particularly effective for an unsaturated surround. A weakly colored surround is apparently capable of inducing a contrast

Figure 5.39 The curves radiating from the white point (W) towards the periphery of the CIE ðx; yÞ diagram represent the chromaticities of the colors induced in a white center field by a concentric surround (see Figure 5.40). The saturation of the induced color increases as purity of the inducing surround changes from from white (W) to maximum purity (þ). When, for instance, the blue surround 5/4 increases in purity, shifting the inducing stimulus color in the direction of the arrow along the dashed line, the saturation of the induced orange color also increases, shifting the color away from white along the fully drawn curve, as indicated by the arrow. A surround color of low purity induces an approximately complementary contrast color, of low saturation, in the center field. Saturated surround colors induce saturated contrast colors but the departure from complementarity is greater than for unsaturated colors. The resulting curves for induced colors bear a strong resemblance to the plots for constant hue with increasing color strength, as seen in Figure 5.28 and 5.29, suggesting a common physiological basis. See Figure 5.40 for experimental setup.

color with a greater chromatic content (chroma) than that of the surround itself (Valberg and Seim, 1983). Chromatic simultaneous contrast is thus amplifying small color differences, making them more visible. Near threshold, this effect is very strong. For instance, when two white colorimetric half-fields match (like the fields A and B in Figure 5.8), and one of them is altered by adding, for instance, a little green to it, it is the other, the physically unchanged field, that becomes redder before you notice the green.

Color induction also contributes to color constancy in complex scenes, a phenomenon that we shall deal with in greater depth in the next section. Consider what happens when, for instance, the illumination becomes redder. A reflecting surface,

In conventional photography you need to use different types of film in artificial light and in daylight. If you don’t, the color of the illuminant will give serious color distortions (for example yellow pictures when using daylight film indoors). Since the same distortions do not occur in vision (a banana looks yellow in bluish daylight as well as in the reddish evening sunset), the visual system must have the ability to neutralize the color of the illuminant, at least within certain limits. The eye adjusts to (adapt to) the light level and to the color of the illuminant so that both the color and the lightness of an object appear largely unchanged.

The color temperature of the illumination also affects the photograph taken with a digital camera. These cameras usually have some kind of automatic adjustment of the white point, using algorithms that seek to infer the color of the ambient light. This may cause problems when one is transferring the image to a computer in an unknown color space.

The color of an object is much less dependent on the spectral distribution of the light coming from it than one tends to believe. It appears that the reflection properties of surfaces relative to their surround are more important for color vision than the actual spectral distributions reaching the eyes. In yellow incandescent light, for instance, one may expect all surfaces to shift their color towards yellow, and slightly bluish surfaces to turn grayish. Yet the white paper still appears white, and blue is still blue. To find a satisfactory quantitative description of this adaptive neutralization of the color of the illuminant is still a challenge.

Leaving temporal and cognitive factors aside, there are some important physical factors that contribute to the color of a surface: its relative spectral power distribution, chromaticity, its contrast to the surroundings and the illumination. Under normal and moderate changes of the illumination, these factors, and a physiological adaptation process that neutralizes the physical changes, ensure approximate color constancy. The details of this process are still unknown, but as we saw above, color induction seems to contribute to it.

Even if a white surface looks white in daylight and in artificial light, we should be aware that food (meat, vegetables, etc.), textiles, ceramic tiles, etc. can change their color in artificial light, although the color distortions may be less than anticipated. Particular spectral distributions of the light sources that illuminate the display stands in many shops may, for instance, boost the redness of meat, or of tomatoes, and enhance the attractiveness of food and vegetables. Such lighting with poor color rendering is frequently used in supermarkets. Poor, but less purposeful color rendering is also typical for some energy-saving illumination.

The von Kries hypothesis

Color induction and adaptation were for a long time explained at the retinal level by a relative reduction of the sensitivity of the cones, but more recent work points also to lateral interactions at several stages of the visual pathway. According to the von Kries

hypothesis (1905), when a white paper looks white regardless of the color of the illumination, this is a consequence of the excitation of the three cone types being adjusted (normalized) to the prevailing illumination. The hypothesis states that sensitivity and excitation is reduced by a factor proportional to the receptor’s initial excitation by the illuminant. For each receptor type, the factor is the same for all wavelengths, and therefore the relative spectral sensitivities of the receptors do not change. Compared with adaptation to equal-energy white light, adaptation to longwavelength red light reduces the sensitivity and excitation of L-cones more than those of M- and S-cones. In real viewing situations, with close to achromatic illumination, the visual system also adjusts to some average luminance and chrominance across the visual field. We may call the latter induction effects lateral adaptation. Lateral adaptation and adaptation to the illuminant may in fact be treated as two different processes. In theory, adaptation by reduced sensitivities accounts for the neutralization of the chromatic component of the illuminant, at least for not too chromatic lights, and for not too strong lateral color-induction effects. If, for a certain surface and a neutral illumination, the excitations of the cones were L, M and S, in the new slightly different adaptation state, they would be changed to:

L0 ¼ L

M0 ¼ M

S0 ¼ S

where ¼ 1=LIll, ¼ 1=MIll and ¼ 1=SIll. The cone excitations LIll, MIll and SIll due to the illuminant refer to those for an ideal, diffuse reflecting white surface under the new illuminant. In this way the cones adapt to every new illumination in such a manner that a white surface keeps equal cone coordinates L0W ¼ MW0 ¼ S0W ¼ 1:0 in that illumination, whereas the coordinates for all other colors will change. This transformation, which continue to give the illumination and a white paper the chromaticity coordinates (13, 13), is often called a centering transformation.

Figure 5.41 demonstrates how one imagines that the von Kries hypothesis works. The color stimulus F has the cone excitations ðL; M; SÞ ¼ ð1; 1; 1Þ. In the (nonrealizable) case where only the M-cones are adapted so that their sensitivity is halved, the vector F will change to F0 in a direction of 50 percent less M excitation, i.e. towards purple. A neutral gray surface affected only by lateral adaptation would thus be expected to appear purple if only the effectiveness of the M-cones was reduced and no other processes (e.g. a greenish illumination) compensated for this change. This is, of course, a hypothetical situation since it is difficult to adapt only one receptor type without affecting the others, but it illustrates the idea. If the same adaptation occurred only in L-cones, the vector would move towards blue–green, and if both L- and M- cone sensitivities were halved, the change would be in the direction of blue. In the theoretical case, where the coefficients , and are determined by the illumination alone and thus are inversely proportional to the excitation of the cones in a given illumination, the result is perfect color constancy. This is so because an increase in the intensity of the illuminant by a factor of 2 would lead to the cones being excited twice

M

F(L, M, S)

F ′(L, 0.5M, S)

L

S

Figure 5.41 Chromatic adaptation can, according to the von Kries hypothesis, be described as a sensitivity reduction of the cones. The adaptation to a colored light (e.g. a chromatic illumination) will affect the receptors differently, depending on how strongly they are excited by the light. The figure illustrates what might happen in a simple (but unrealistic) case where green light reduces the sensitivity of the M-cone by a factor of 2 and leaves the sensitivity of the other receptors unchanged. The anticipated effect would be that the vector F changes to vector F0 due to less excitation of the M cone. An embedded region that originally looked white, and which is not illuminated by the green light, would now appear purple. If, on the other hand, the embedded white surface were also illuminated by the greenish light, it would remain white.

as much, and the ensuing adaptation would then reduce their sensitivity to 50 percent of its original value. Taken together, excitation, being the product of power and sensitivity, would be unchanged, and thus the vector representing a white stimulus would also be unchanged. In other words, the von Kries hypothesis states that, if sensitivity is reduced by the same factor as the excitation is increased, the chromaticity of the illumination would be exactly compensated for.

Such total adaptation to the color of the illuminant is likely to occur only when its chromaticity deviates little from white. Even the transition from daylight to incandescent light is too large a color shift for this hypothesis to hold true; computing color shifts for this situation according to the simple von Kries scheme above gives results that do not agree with our experience. Therefore, the von Kries hypothesis can, at most, be a first linear approximation of a complex, probably nonlinear, process. Despite this, the von Kries hypothesis has played a prominent role within lighting engineering, and it is still used in the absence of a better method.

Color rendering

The CIE characterizes the color rendering of light sources by a single number, the color rendering index, CRI, computed as the average index of eight standard color test samples. A value of 100 is regarded as being excellent and a value below 70 is rather poor color rendering. However, the basis for computing the CRI is the long

obsolete von Kries adaptation hypothesis, and the computations do not compare well with subjective judgements (Valberg et al., 1979). Despite this rather unsatisfactory situation, the von Kries hypothesis is used by the lighting industry to calculate a CRI of light sources. This index is based on a calculation of the color shifts that occur when the illumination is changed from a standard source to the illumination under test. A standard source can be either the daylight or a blackbody radiator of the nearest color temperature (the temperature that gives a black-body color most similar to that of the test light). Manufacturers of light sources give the CRI in their catalogues. An index between 90 and 100 signifies a very good color rendering.

The reason why such an index is needed is that color constancy is only approximate, not absolute. Therefore, the pressing practical problem is to predict the deviations from constancy of a given illumination. Over the years there has been an abundance of experiments quantifying the color shifts for the most common light sources, in both simple and complex viewing situations, but the experimental results still await a good theoretical model. The centering transformation mentioned above for cone excitations can in many cases give a good first approximation to these data, and the approximation works better in broad-band, weakly chromatic illumination than for strongly chromatic light sources.

Apart from these problems, using a single value to characterize color rendering, such as the CRI, is not adequate for many modern light sources. For instance, many fluorescent lamps have a rather complex spectral distribution with many narrow spectral bands that may lead to unexpected shifts of surface colors and to problems with metamerism. It would therefore be an advantage to know, for each new light source, the color shifts of individual samples on a color circle, for instance for 24 hues of high saturation around the color circle, and for another circle with medium saturation. Such additional information would meet the requirement of being easily understood, and it would help the designers in their efforts to create esthetic environments with the help of light and color.

The centering transformation

Below we give an example of a centering transformation as it is used, for instance in TV broadcasting, to compensate for the chromaticity of (weak chromatic) illumination (although strictly it should be applied only for lateral adaptation), let us take a set of tristimulus values R, G and B that are normalized so that RW ¼ GW ¼ BW ¼ 1:0 for an ideal, diffusely reflecting white surface (made for instance from magnesium oxide or barium sulphate). R, G and B may be thought of as general tristimulus values; they can be either the tristimulus values of an additive color mixture, or the corresponding cone excitations L, M and S. Let Y signify luminance.

When changing to a new illumination, C, the white surface will have the tristimulus values RC, GC and BC. If we want the white surface to keep its original tristimulus values

(1,1,1) in the new illumination, this can be achieved by dividing all tristimulus values by the tristimulus values for the new white surface. The new ‘centered’ tristimulus values are R0 ¼ R=RC, G0 ¼ G=GC and B0 ¼ B=BC. This is a simple color correction. Let us look at an example.

Table 5.1

The original color coordinates of Table 5.1 are shown in an opponent diagram in Figure 5.42(a), and the transformed coordinates, centered to the new Ill. C, are given in Table 5.2 and Figure 5.42(b). In Figure 5.42(b), the new white point, C 0, is at the origin. The old white chromaticity point, W (illuminated by the original illuminant, not Ill. C ) has moved towards blue (W 0) due to lateral adaptation. This is as expected since the illumination C is perceived as orange when adapted to W and induction effects from extended surrounds are strong. A physical stimulus F2 changes from being reddish in Figure 5.42(a) to become reddish-blue in Figure 5.42(b). The color stimulus F1 does not change much.

Table 5.2

Edwin Land’s retinex hypothesis

In the case where the tristimulus values R, G, and B above represent the cone excitations L, M and S, the centering transformation of Table 5.2 would correspond to the von Kries adaptation hypothesis. The sensitivities of the receptor types would have changed by factors equal to 1=RC ¼ , 1=GC ¼ and 1=BC ¼ .

A similar description of color adaptation has been used by McCann et al. (1976) and Land (1983) in their retinex hypothesis. In the original version, all relative cone excitations were normalized to their values for a white surface, as in Tables 5.1 and 5.2. The assumption was that the surface with the highest luminance or reflection

W´

Figure 5.42 An example of how a centering of tristimulus values may give an approximately quantitative account of chromatic adaptation. Centering means to place the chromaticity of the prevailing illumination at the origin of the coordinate system. Changing the chromaticity of the illuminant from W to another, and slightly different illuminant, C (e.g. from daylight to incandescent light), will change the color coordinates of all objects illuminated. Centering shifts the ‘neutral point’ of the diagram, so that it coincides with the new illuminant. This manipulation of color space might, at a first glance, seem to explain why a white surface stays white regardless of small color shifts in the illumination. The centering, bringing illuminant C into the origin of the diagram, leads to close to parallel shifts of the chromaticity of all the other surfaces as well (arrows in the figure). However, this simple description of color shifts, as a result of the centering of tristimulus values (or even of cone excitations) to the new illuminant, is not quite in accordance with experimental data. However, in want of a better hypothesis, it can serve as a simple rule of thumb. Edwin Land’s original retinex hypothesis was one such centering transformation.

factor contributes the most to adaptation. This led to a result that was identical to a centering transformation and to the von Kries hypothesis. Thus, the retinex and the von Kries hypotheses were essentially the same and suffered from the same weaknesses (Judd, 1960).

Later, Land changed the computational procedure. In the centering operation, the tristimulus values for the white surface were replaced by the geometrical mean of the cone excitations for all colored areas within the field of view. For a many-colored, complex scene this average came close to that for a gray stimulus, and this was now

taken as the adaptation reference. All cone excitations were centered to (divided by) these averaged values, and such ratios changed relatively little when the illumination changed color. The increased redness of a banana in the evening sun is neutralized by the increased redness of the surrounding environment. In his impressive demonstrations of color constancy, Land used a composite image with many different sizes and colors, a so-called ‘Mondrian’ (Figure 5.43), named after the Dutch painter Piet Mondrian.

Figure 5.43 An example of a complex Mondrian of the kind used by Edwin Land to demonstrate his retinex hypothesis. (See also color plate section.)

However, many psychophysical experiments have shown that the retinex computations do not lead to the right solution. Constancy is not absolute, and there are significant differences between the experimentally determined color shifts of a surface and the color coordinates that follow from the retinex theory. The computational method leads to a result that resembles what happens under simultaneous contrast: an environment that has become reddish due to the illumination induces blue–green into darker, less reflecting areas, and the induced blue–green neutralizes some of the increased redness from the illumination. If these two opposite processes were linear and of equal magnitudes, the result would have been absolute color constancy. However, there is neither a complete neutralization of color strength, nor of hue. The deviations that occur are larger the more saturated the illuminant.

What would happen if we replaced the complex Mondrian outside the green area no. 1 in Figure 5.43 with a homogeneous gray area? The retinex hypothesis would predict that the green color of the no. 1 area would be maintained, provided that the surrounding gray gives rise to the same three cone excitations as the geometrical mean of all Mondrian patches. This is often called the ‘gray world hypothesis’. Experiments have shown that it is indeed possible, by trial and error, to find a gray that, when replacing a particular Mondrian, does not change the color of area no. 1. Yet this surrounding gray is not that which is predicted by the geometrical mean, as

required by the retinex hypothesis (Valberg and Lange Malecki, 1990). This is probably not too surprising, because we know for instance that proximity plays a major role in color induction. Areas nearby have a stronger inducing effect than those further away. This fact was not taken into account in the retinex hypothesis. All Mondrian patches were weighted equally in the computation of the average excitation values regardless their distance.

We can summarize Land’s proposal for the normalization of the cone excitations in a Mondrian as follows: first take the ratio of the cone excitations L, M and S between areas that are adjacent (it was actually suggested to follow a path like the one shown in Figure 5.43, but this is not necessary). If we disregard threshold, for the L-cone the retinex calculates:

L01 ¼ ðL1=L2ÞðL2=L3Þ . . . ðLn 1=LnÞ ¼ L1=Ln

or

log L01 ¼ log L1 log Ln

Then summate the logarithms of all these ratios, L0i, over all n fields in the Mondrian, and compute the geometrical mean:

X

log L01 ¼ ð1=nÞ½n log L1 log Li&

X

¼ log L1 ð1=nÞ log Li

The same procedure is repeated for the other cone excitations M and S. The normalized cone excitations L0, M0 and S0 will be the new color coordinates for field no. 1 in the same way as R0, G0 and B0 in Table 5.2. The values

X X X

ð1=nÞ log Li ð1=nÞ log Mi ð1=nÞ log Si

are the logarithms of the geometric means of the cone excitations of all fields surrounding no. 1 in Figure 5.43.

An evenly distributed illumination, let us say a reddish one, leads to exactly the same changes in cone excitations for area no. 1 as for every field surrounding it. In the equations above, this will be factored out. Physiologically this means that the change in one field is neutralized by its surroundings. The ‘redness’ of the surround is subtracted from the ‘redness’ of the field in the logarithmic expression, and the net result is no additional effect by the new illumination on the relative cone excitations. Consequently, said Land, since this triplet of relative cone excitations of a patch remains unchanged, color constancy is the result.

Land published his first demonstrations and color vision theory in 1959 in a series of articles in Proceedings of the National Academy of Sciences (Land, 1959). In what turned out to be a consequence of simultaneous color contrast and induction, he

described how to produce all hues by only mixing two colored lights in addition to white. This he considered a proof that the Young–Helmholtz trichromatic theory was wrong. Land’s alternative theory was more or less refuted by Judd and other critics. For many years, there was little debate about Land’s theory until his ideas experienced a renaissance in the 1980s. Land entered the scene at several international conferences with his Mondrian demonstrations and conducted a spectacular ‘color show’ with great bravura. This revival of interest initiated a series of neurophysiological measurements of the response to color stimuli of single cells in the retina and in the brain, using macaque monkeys as the experimental animal. However, in this wave of enthusiasm, the attitude towards Land’s ideas was often somewhat uncritical (see the next chapter, Crick, 1994; and Zeki, 1993). All of Land’s papers are published in Science, Education and Industry, Vols I–III, IS&T, 1993.

The problem that remains to be explained may be formulated as follows: how can one best separate the physical change in the direct excitation of cones from compensatory, indirect lateral processes like induction? When illumination changes, both object and surround change color coordinates. Even though adaptation and lateral induction contribute significantly to neutralizing the effect of this physical change, these processes do not suffice to cancel it completely. Most experiments designed to test the von Kries hypothesis have indicated that one needs to search for alternative ways to describe chromatic adaptation and color constancy. The quality and strength of the induction effects, represented by the curves for the induced colors in Figure 5.39, point to involvement of neural processes that are nonlinearly related to the stimulus changes (since a linear change in cone excitation would have been represented by straight lines). In natural viewing situations, simultaneous contrast (induction) and adaptation can be considered two sides of the same coin, and the nonlinearity displayed in Figure 5.39 shows that both processes arise beyond the linear excitation process that is so fundamental in color metrics.

On the background of Valeton and van Norren’s measurements of receptor potentials under several conditions of light adaptation [Figure 4.15(b)], an alternative model would associate adaptation with changes in the half-saturation constants, , in the formula for cone responses (see p. 164). It would have been of great help to know more about the dependence of on adaptation level. Exploratory electrophysiological measurements on cones and on cone-opponent cells, have shown that, in ‘M–L’ and ‘L–M’ opponent cells, chromatic adaptation can be modeled by adjusting the halfsaturation constants L and M of the cones that have inputs to the cell.

A possible further step towards a better model of chromatic adaptation might be to formulate excitation and inhibition in double-opponent cortical cells (such cells will be described on p. 393). Double-opponent cells are thought to also contribute to color constancy, because in such cells center and surround together are able to neutralize the chromatic component of the illumination. Thus, color constancy seems to be a composite phenomenon that incorporates adaptation and simultaneous contrast, with contributions from several processing stages in the visual pathway.