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Figure 11: Left: luminous efficiency function after [9].Right: calculation of luminance from the luminous efficiency function and the spectral power distribution for illuminant D65 [6]. We say that light, or visible radiation, ranges from about 380 to 780 nanometres in wavelength, bu in fact wavelengths towards the limits of this range are barely visible, and the response of the humat visual system increases from these limits up to the middle of the range, peaking in the wavelength perceived as yellow-green. This curve showing the responsiveness of the visual system of a standart human observer to different wavelengths is called the luminous efficiency function (Figure 11, left). Th amount of of light that an area emits, transmits or reflects is quantified colorimetrically as luminance the physical power of the light weighted wavelength-by-wavelength by the responsiveness of the humat visual system (Figure 11, right). Two lights adjusted to match in brightness when compared in certait ways, notably by showing no flicker when alternated very rapidly (a method called flicker photometry or by finding the point at which they exhibit a minimally distinct border, would be expected to have th: same luminance. (Note: if these lights differ in colour they might be perceived to differ in brightnes: when compared by other methods, as will be discussed in Part Two). Be eet weenie cornet: abies ex lk? nomeccoember co alco eek ecleerotanl ice exceeded le niste: beewertver: oo mews

Figure 11 Left: luminous efficiency function after [9].Right: calculation of luminance from the luminous efficiency function and the spectral power distribution for illuminant D65 [6]. We say that light, or visible radiation, ranges from about 380 to 780 nanometres in wavelength, bu in fact wavelengths towards the limits of this range are barely visible, and the response of the humat visual system increases from these limits up to the middle of the range, peaking in the wavelength perceived as yellow-green. This curve showing the responsiveness of the visual system of a standart human observer to different wavelengths is called the luminous efficiency function (Figure 11, left). Th amount of of light that an area emits, transmits or reflects is quantified colorimetrically as luminance the physical power of the light weighted wavelength-by-wavelength by the responsiveness of the humat visual system (Figure 11, right). Two lights adjusted to match in brightness when compared in certait ways, notably by showing no flicker when alternated very rapidly (a method called flicker photometry or by finding the point at which they exhibit a minimally distinct border, would be expected to have th: same luminance. (Note: if these lights differ in colour they might be perceived to differ in brightnes: when compared by other methods, as will be discussed in Part Two). Be eet weenie cornet: abies ex lk? nomeccoember co alco eek ecleerotanl ice exceeded le niste: beewertver: oo mews

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Figure 1: Left: Plan view of colours represented in the Munsell Book of Color Glossy Edition, showing colours of the lightest chips for each hue and chroma. Middle: hue page for Munsell hue 10R, showing variations in Munsell value (lightness) and Munsell chroma. The Munsell notation 10R 6/14 identifies the chip on the 10R hue page with a Munsell value of 6 and a Munsell chroma of 14. Right: Alternative classification of colours on a hue page, according to the NCS-defined attributes of blackness and chromaticness, plus the relationship to the attribute of brilliance. The perceived colours of lights and objects can be described in terms of various sets of three attributes iat can each be visualised as the three dimensions of a colour space. These perceived colour attributes re the subject of Part Two, but some of the most important terms will be briefly introduced here. The ue of a colour is the most similar step in the scale of red-yellow-green-blue-red and their intermediates. olours possessing hue are called chromatic and those devoid of hue are called achromatic. One set of 1ree attributes that is widely used to describe colours perceived as belonging to objects comprises hue, ghtness (also called value, greyscale value, or tone; the most similar step on a scale between black and hite) and chroma (chromatic intensity perceived as belonging to an object). These three CIE-defined ttributes can be quantified in terms of the hue, lightness and chroma scales of the Munsell system tigure 1) or of other colour spaces such as CIE L*a*b* in the form CIE L*C*h. Colours of objects can Iso be described and specified using other sets of three attributes, including the NCS-defined attributes f hue, blackness (resemblance to pure black) and chromaticness (resemblance to full colour). The Jlours of objects perceived to emit light lie off the scale of blackness and may be said to exhibit rilliance. Colours of lights can be described in terms of hue, brightness (perceived intensity of light) nd colourfulness (perceived chromatic intensity of light), or hue, brightness and saturation (the olourfulness of a light relative to its brightness, which amounts to its perceived freedom from a white ght component). Newton [5] showed that the reason why light forms what he named a spectrum when it passes through a prism is because it is broken up into a series of components (we would now say different wavelengths) that appear different colours. Yet when we see a light compounded of different wavelengths, we don’t experience multiple colour perceptions corresponding to these multiple components; we see a single colour. Crucially, Newton showed that the colour of an isolated light can be predicted from the overall balance or what he called the “center of gravity” of its spectral components in a two-dimensional circuit of directions of bias relative to light perceived to be white (Figure 2, top left). The hue of an isolated light could be predicted from the direction of bias relative to white light, Newton [5] showed that the reason why light forms what he named a spectrum when it passes
Figure 1: Left: Plan view of colours represented in the Munsell Book of Color Glossy Edition, showing colours of the lightest chips for each hue and chroma. Middle: hue page for Munsell hue 10R, showing variations in Munsell value (lightness) and Munsell chroma. The Munsell notation 10R 6/14 identifies the chip on the 10R hue page with a Munsell value of 6 and a Munsell chroma of 14. Right: Alternative classification of colours on a hue page, according to the NCS-defined attributes of blackness and chromaticness, plus the relationship to the attribute of brilliance. The perceived colours of lights and objects can be described in terms of various sets of three attributes iat can each be visualised as the three dimensions of a colour space. These perceived colour attributes re the subject of Part Two, but some of the most important terms will be briefly introduced here. The ue of a colour is the most similar step in the scale of red-yellow-green-blue-red and their intermediates. olours possessing hue are called chromatic and those devoid of hue are called achromatic. One set of 1ree attributes that is widely used to describe colours perceived as belonging to objects comprises hue, ghtness (also called value, greyscale value, or tone; the most similar step on a scale between black and hite) and chroma (chromatic intensity perceived as belonging to an object). These three CIE-defined ttributes can be quantified in terms of the hue, lightness and chroma scales of the Munsell system tigure 1) or of other colour spaces such as CIE L*a*b* in the form CIE L*C*h. Colours of objects can Iso be described and specified using other sets of three attributes, including the NCS-defined attributes f hue, blackness (resemblance to pure black) and chromaticness (resemblance to full colour). The Jlours of objects perceived to emit light lie off the scale of blackness and may be said to exhibit rilliance. Colours of lights can be described in terms of hue, brightness (perceived intensity of light) nd colourfulness (perceived chromatic intensity of light), or hue, brightness and saturation (the olourfulness of a light relative to its brightness, which amounts to its perceived freedom from a white ght component). Newton [5] showed that the reason why light forms what he named a spectrum when it passes through a prism is because it is broken up into a series of components (we would now say different wavelengths) that appear different colours. Yet when we see a light compounded of different wavelengths, we don’t experience multiple colour perceptions corresponding to these multiple components; we see a single colour. Crucially, Newton showed that the colour of an isolated light can be predicted from the overall balance or what he called the “center of gravity” of its spectral components in a two-dimensional circuit of directions of bias relative to light perceived to be white (Figure 2, top left). The hue of an isolated light could be predicted from the direction of bias relative to white light, Newton [5] showed that the reason why light forms what he named a spectrum when it passes
Figure 2: Above: “center of gravity” of a whitish orange, a white, and a spectral orange light, after Newton [5, Book 1, Part 2, fig. 11]. Newton’s accompanying text explaining his “center of gravity” principle reads: “Find the common center of gravity of all those Circles p, q, r, s, t, v, x. Let that center be Z; and from the center of the Circle ADF, through Z to the circumference, drawing the right Line OY, the place of the Point Y in the circumference shall shew the Colour arising from the composition of all the Colours in the given mixture, and the Line OZ shall be proportional to the fulness or intenseness of the Colour, that is, to its distance from whiteness” [5, Book 1, Part 2, p. 115]. The amounts of each spectral component, represented in Newton’s diagram by the size of the small circles, are now represented as a spectral power distribution, a plot of the wavelength-by- wavelength distribution of radiant power, measured in microwatts per cm2 per nanometre. Below left: spectral power distributions of three lights that would plot at Z, O and Y in Newton’s circle: a whitish orange illuminant, CIE Illuminant A, representative of tungsten illumination (left), a white illuminant, CIE Illuminant D65, representative of noon daylight (middle), and spectral orange (right). Lower right: spectral power distribution of the light emitted by the saturated orange dot “Y” on an iPhone X screen (right) after [6]. and what he called the “fulness or intenseness of the Colour” or its “distance from whiteness”, now called its saturation, could be predicted from the amount of bias. Another way of saying this is that the colour of an isolated light is the way in which we perceive the overall balance of its spectral components relative to that of light perceived to be white, such as daylight. Whitish orange as the colour of an isolated light is the way in which we perceive an overall balance of spectral components biased in a certain way relative to daylight, and white as the colour of an isolated light is the way in which we perceive an overall balance of the same spectral components similar to that of daylight (Figure 2, top middle). balance of the same spectral components similar to that of daylight (Figure 2, top middle).
Figure 2: Above: “center of gravity” of a whitish orange, a white, and a spectral orange light, after Newton [5, Book 1, Part 2, fig. 11]. Newton’s accompanying text explaining his “center of gravity” principle reads: “Find the common center of gravity of all those Circles p, q, r, s, t, v, x. Let that center be Z; and from the center of the Circle ADF, through Z to the circumference, drawing the right Line OY, the place of the Point Y in the circumference shall shew the Colour arising from the composition of all the Colours in the given mixture, and the Line OZ shall be proportional to the fulness or intenseness of the Colour, that is, to its distance from whiteness” [5, Book 1, Part 2, p. 115]. The amounts of each spectral component, represented in Newton’s diagram by the size of the small circles, are now represented as a spectral power distribution, a plot of the wavelength-by- wavelength distribution of radiant power, measured in microwatts per cm2 per nanometre. Below left: spectral power distributions of three lights that would plot at Z, O and Y in Newton’s circle: a whitish orange illuminant, CIE Illuminant A, representative of tungsten illumination (left), a white illuminant, CIE Illuminant D65, representative of noon daylight (middle), and spectral orange (right). Lower right: spectral power distribution of the light emitted by the saturated orange dot “Y” on an iPhone X screen (right) after [6]. and what he called the “fulness or intenseness of the Colour” or its “distance from whiteness”, now called its saturation, could be predicted from the amount of bias. Another way of saying this is that the colour of an isolated light is the way in which we perceive the overall balance of its spectral components relative to that of light perceived to be white, such as daylight. Whitish orange as the colour of an isolated light is the way in which we perceive an overall balance of spectral components biased in a certain way relative to daylight, and white as the colour of an isolated light is the way in which we perceive an overall balance of the same spectral components similar to that of daylight (Figure 2, top middle). balance of the same spectral components similar to that of daylight (Figure 2, top middle).
Figure 3: Left: Cone fundamentals of Stockman and Sharpe (2 degree, linear, normalised to equal height) [9]. These curves show the effective relative response of each cone cell type to different wavelengths of light reaching the eye, as opposed to the retina (that is, they take account of the filtering of short wavelengths within the eye). Middle and right: diagrams explaining L vs M and S vs LM cone opponent processing and the cone opponent responses to individual wavelengths of light, all after [10].
Figure 3: Left: Cone fundamentals of Stockman and Sharpe (2 degree, linear, normalised to equal height) [9]. These curves show the effective relative response of each cone cell type to different wavelengths of light reaching the eye, as opposed to the retina (that is, they take account of the filtering of short wavelengths within the eye). Middle and right: diagrams explaining L vs M and S vs LM cone opponent processing and the cone opponent responses to individual wavelengths of light, all after [10].
Figure 4: Left: Representative RGB digital primaries each stimulate one cone type more than the other two and thereby each evoke a strong cone opponent response. Middle: mixtures of these primaries in different proportions span the full circuit of cone opponent response combinations. Right: This two-dimensional circuit of cone-opponent response combinations, reflecting a two-dimensional circuit of directions of detectable bias towards long, middle, short, and long and short wavelengths respectively, is ultimately perceived as the two- dimensional circuit of hues perceived by colour-normal humans. See caption to Figure 3 for sources for Figure 4, left and middle.
Figure 4: Left: Representative RGB digital primaries each stimulate one cone type more than the other two and thereby each evoke a strong cone opponent response. Middle: mixtures of these primaries in different proportions span the full circuit of cone opponent response combinations. Right: This two-dimensional circuit of cone-opponent response combinations, reflecting a two-dimensional circuit of directions of detectable bias towards long, middle, short, and long and short wavelengths respectively, is ultimately perceived as the two- dimensional circuit of hues perceived by colour-normal humans. See caption to Figure 3 for sources for Figure 4, left and middle.
Figure 5: In the image on the left we perceive a cube having a uniform orange object colour, as if it were painted all over with the same orange paint, even though the image areas depicting planes A to C respectively appear progressively brighter and more colourful. Similarly, we perceive the lighter-coloured areas of the floor as being white things, even though the corresponding image areas appear variably bright. We do not see these variations in brightness and colourfulness as belonging to the objects themselves, but instead we instantly and automatically attribute them to variations in the illumination. Right: patterns of uniform orange, black and white object colours (below) and of illumination of varying brightness (above), that we perceive superimposed in the image on the left. perceptions, we perceive object colours to be located outside us in objects themselves, as in the uniform black, white and orange object colours that we perceive to be located in the tiles and cube depicted in Figure 5, left, even though these objects are physically non-existent. This last observation can help students to accept that the colours they perceive to be located in actual objects are similarly not located in those objects, but are perceptions that we project onto objects.
Figure 5: In the image on the left we perceive a cube having a uniform orange object colour, as if it were painted all over with the same orange paint, even though the image areas depicting planes A to C respectively appear progressively brighter and more colourful. Similarly, we perceive the lighter-coloured areas of the floor as being white things, even though the corresponding image areas appear variably bright. We do not see these variations in brightness and colourfulness as belonging to the objects themselves, but instead we instantly and automatically attribute them to variations in the illumination. Right: patterns of uniform orange, black and white object colours (below) and of illumination of varying brightness (above), that we perceive superimposed in the image on the left. perceptions, we perceive object colours to be located outside us in objects themselves, as in the uniform black, white and orange object colours that we perceive to be located in the tiles and cube depicted in Figure 5, left, even though these objects are physically non-existent. This last observation can help students to accept that the colours they perceive to be located in actual objects are similarly not located in those objects, but are perceptions that we project onto objects.
Figure 6: Left: Spectral reflectance curves for selected artists’ paints [13], showing correlation of overall profile with perceived colour. For example, white, grey and black paints have a spectral reflectance that is very high, intermediate and very low respectively and about equal in their long-, middle- and short-wavelength components, while high-chroma paints have a spectral reflectance that is strongly biased towards certain wavelengths. Right: circuit of directions of overall bias of spectral reflectance towards long-, middle-, short- or long- and short-wavelengths of artists’ paints and its correlation with hue. By shining a spectrum on various artists’ pigments, Newton advanced the study of object colours by finding that their physical basis, what he called “Colours in the Object”, lay in the object’s “Disposition to reflect this or that sort of Rays more copiously than the rest”, which we would now call the object’s spectral reflectance’. It is important to note that the term spectral reflectance refers to the inherent reflectance of an object for each wavelength of light, and not to the spectrum of wavelengths that an object reflects under a particular light source. Like all perceived colours, the colour perceived to belong to an object can be greatly influenced by a variety of environmen tal and individual factors in addition to the object’s spectral properties. (Newton also made a precocious observation in relation to these factors by showing that an object that appeared grey in daylig pigments - could be made to appear white if locally illuminated when we can freely examine an object in daylight, the colour we usually a very good indication of the object’s overall spectral reflect ht — a mixture of powdered artists’ in a darkened room). Nevertheless, perceive as belonging to the object is ance, meaning its spectral reflectance at the level of its long-, middle-, and short-wavelength components (Figure 6). (We understandably tend to think of this perceived colour of the object freely examined in daylight — the illumination in which our colour vision is most effective - as being the object’s seemingly intrinsic colour).
Figure 6: Left: Spectral reflectance curves for selected artists’ paints [13], showing correlation of overall profile with perceived colour. For example, white, grey and black paints have a spectral reflectance that is very high, intermediate and very low respectively and about equal in their long-, middle- and short-wavelength components, while high-chroma paints have a spectral reflectance that is strongly biased towards certain wavelengths. Right: circuit of directions of overall bias of spectral reflectance towards long-, middle-, short- or long- and short-wavelengths of artists’ paints and its correlation with hue. By shining a spectrum on various artists’ pigments, Newton advanced the study of object colours by finding that their physical basis, what he called “Colours in the Object”, lay in the object’s “Disposition to reflect this or that sort of Rays more copiously than the rest”, which we would now call the object’s spectral reflectance’. It is important to note that the term spectral reflectance refers to the inherent reflectance of an object for each wavelength of light, and not to the spectrum of wavelengths that an object reflects under a particular light source. Like all perceived colours, the colour perceived to belong to an object can be greatly influenced by a variety of environmen tal and individual factors in addition to the object’s spectral properties. (Newton also made a precocious observation in relation to these factors by showing that an object that appeared grey in daylig pigments - could be made to appear white if locally illuminated when we can freely examine an object in daylight, the colour we usually a very good indication of the object’s overall spectral reflect ht — a mixture of powdered artists’ in a darkened room). Nevertheless, perceive as belonging to the object is ance, meaning its spectral reflectance at the level of its long-, middle-, and short-wavelength components (Figure 6). (We understandably tend to think of this perceived colour of the object freely examined in daylight — the illumination in which our colour vision is most effective - as being the object’s seemingly intrinsic colour).
Figure 7: Simulation of a scene under white, pinkish, and monochromatic red illumination. Under pinkish illumination colour discrimination is impaired, but we may still perceive some objects as being white and grey (the colours they appear in daylight) by unconsciously attributing the pinkish colour of these areas to the illumination rather than to the objects. Under monochromatic illumination, however, we can perceive as object colours only variations in the reflectance of the single wavelength present. have a decreasing influence on our perception of colour. d t d t Our ability to perceive the overall spectral reflectance of an object as its colour is most effective in ayligh hus ap ayligh t t or in lighting having a spectral distribution that is similarly balanced both on a broad scale, pearing “white” or achromatic, and reasonably even on a small scale, thus having a high Colour Rendering Index (CRI). Nevertheless, under illumination that is somewhat biased spectrally relative to t, the colours we see objects as having exhibit a degree of constancy. This degree of constancy arises in part because our visual system has the capacity to adapt, to a degree, to the spectral bias, so hat the illumination appears less strongly coloured than it would otherwise, and also, quite apart from his, because our visual system has the ability to automatically and unconsciously parse the scene to some extent into colours relating to the illumination and to the objects, such that we might perceive some components of the pinkish scene in the upper right of Figure 7 to be white and grey objects under pinkish illumination. Nevertheless, our capacity to distinguish objects based on their spectral reflectance diminishes as the spectral bias of the illumination increases, and under monochromatic illumination we perceive as object colours only the objects’ reflectance of the single wavelength present (Figure 7, lower right).
Figure 7: Simulation of a scene under white, pinkish, and monochromatic red illumination. Under pinkish illumination colour discrimination is impaired, but we may still perceive some objects as being white and grey (the colours they appear in daylight) by unconsciously attributing the pinkish colour of these areas to the illumination rather than to the objects. Under monochromatic illumination, however, we can perceive as object colours only variations in the reflectance of the single wavelength present. have a decreasing influence on our perception of colour. d t d t Our ability to perceive the overall spectral reflectance of an object as its colour is most effective in ayligh hus ap ayligh t t or in lighting having a spectral distribution that is similarly balanced both on a broad scale, pearing “white” or achromatic, and reasonably even on a small scale, thus having a high Colour Rendering Index (CRI). Nevertheless, under illumination that is somewhat biased spectrally relative to t, the colours we see objects as having exhibit a degree of constancy. This degree of constancy arises in part because our visual system has the capacity to adapt, to a degree, to the spectral bias, so hat the illumination appears less strongly coloured than it would otherwise, and also, quite apart from his, because our visual system has the ability to automatically and unconsciously parse the scene to some extent into colours relating to the illumination and to the objects, such that we might perceive some components of the pinkish scene in the upper right of Figure 7 to be white and grey objects under pinkish illumination. Nevertheless, our capacity to distinguish objects based on their spectral reflectance diminishes as the spectral bias of the illumination increases, and under monochromatic illumination we perceive as object colours only the objects’ reflectance of the single wavelength present (Figure 7, lower right).
Figure 8: In Edward Adelson’s checker shadow illusion (left, ©1995, Edward H. Adelson), the image areas labelled A and B physically match and thus have equal luminance, but it is difficult to perceive the light from these areas as equal in brightness. We could of course compare the luminance of these areas veridically by masking out the rest of the scene, but interestingly we can achieve the same result if we break the representational spell of the image merely by introducing targets seen as being outside the depicted illumination. This suggests that our difficulty in comparing the image areas stems from our attention being held by the perceived colours of the virtual objects depicted in the scene at the expense of colours relating to the actual image areas [17]. Colorimetric specification of lights and objects can be an area of confusion in the broader colour
Figure 8: In Edward Adelson’s checker shadow illusion (left, ©1995, Edward H. Adelson), the image areas labelled A and B physically match and thus have equal luminance, but it is difficult to perceive the light from these areas as equal in brightness. We could of course compare the luminance of these areas veridically by masking out the rest of the scene, but interestingly we can achieve the same result if we break the representational spell of the image merely by introducing targets seen as being outside the depicted illumination. This suggests that our difficulty in comparing the image areas stems from our attention being held by the perceived colours of the virtual objects depicted in the scene at the expense of colours relating to the actual image areas [17]. Colorimetric specification of lights and objects can be an area of confusion in the broader colour
ee ee ee ee eee nee i nce ee En on Onn” on sea ee eT een” eee ene en ee nn nn no in ne ann see en ee nen ee ne ei DESDE! differences by ignoring physical differences that are not perceivable to human colour vision. Figure 9 shows an intuitive, nonmathematical way of explaining the rationale for the colorimetry o: lights. I begin by explaining that if my computer screen could emit a sufficient range of light intensities I could visually match the light reaching my eye from most points in my environment with a light on m} screen, and so could represent those lights in a cubic RGB colour space according to the R, G and FE components of the matching lights, much as a digital camera is designed to do in a different way However, while we need three dimensions to describe the colour of an object, for many purposes we car consider the colour of a light to be separate from its brightness, and correspondingly we can specify the colour of a light for many purposes using only two dimensions. If I were to leave out the total amount of light (as did Newton in his circle), I could represent these RGB quantities as a two-dimensiona triangle, showing only the ratio of the matching long-, middle- and short-wavelength primaries, R, GC and B. A two-dimensional diagram of this kind, showing the ratio of three primaries but not theit absolute intensity, is called a chromaticity diagram*4. But whatever R, G and B primaries my screer uses, some highly saturated lights would be outside the range that I could match directly, and so woulc lie outside the cube and outside the triangle. Figure 9: Nonmathematical explanation of the CIE 1931 x,y chromaticity diagram by analogy with an RGB chromaticity diagram (see text). Graphics exported from ColorSpace by Philippe Colantoni and Maxwell Triangle by efg2.com (both now unavailable). lie outside the cube and outside the triangle.
ee ee ee ee eee nee i nce ee En on Onn” on sea ee eT een” eee ene en ee nn nn no in ne ann see en ee nen ee ne ei DESDE! differences by ignoring physical differences that are not perceivable to human colour vision. Figure 9 shows an intuitive, nonmathematical way of explaining the rationale for the colorimetry o: lights. I begin by explaining that if my computer screen could emit a sufficient range of light intensities I could visually match the light reaching my eye from most points in my environment with a light on m} screen, and so could represent those lights in a cubic RGB colour space according to the R, G and FE components of the matching lights, much as a digital camera is designed to do in a different way However, while we need three dimensions to describe the colour of an object, for many purposes we car consider the colour of a light to be separate from its brightness, and correspondingly we can specify the colour of a light for many purposes using only two dimensions. If I were to leave out the total amount of light (as did Newton in his circle), I could represent these RGB quantities as a two-dimensiona triangle, showing only the ratio of the matching long-, middle- and short-wavelength primaries, R, GC and B. A two-dimensional diagram of this kind, showing the ratio of three primaries but not theit absolute intensity, is called a chromaticity diagram*4. But whatever R, G and B primaries my screer uses, some highly saturated lights would be outside the range that I could match directly, and so woulc lie outside the cube and outside the triangle. Figure 9: Nonmathematical explanation of the CIE 1931 x,y chromaticity diagram by analogy with an RGB chromaticity diagram (see text). Graphics exported from ColorSpace by Philippe Colantoni and Maxwell Triangle by efg2.com (both now unavailable). lie outside the cube and outside the triangle.
Figure 10: Three spectral power distributions, after [6], having the same overall balance at the level of their long-, middle-, and short-wavelength components from the point of view of the human visual system, and thus matching in colour (appearing white as an isolated light), and plotting at the same point (O) in the CIE 1931 x,} chromaticity diagram. Compare concepts of dominant wavelength and purity to Newton’s predictors of hue and saturation. The CIE x,y diagram is not the latest but is still the most familiar descendent of Newton’s colour circle. Location in the x,y chromaticity diagram represents the overall balance of wavelengths in a light at the level of its long-, middle- and short-wav: a mathematically defined “standard” human elength components, as detected by the visual system of observer. As was already implicit in Newton’s circle, physically different mixtures of spectral components can evoke the same perceived colour if they have the same “center of gravity”, or overall balance spectral distributions that appear white as iso daylight, CIE illuminant F7, representative of and a specific white LED screen adjusted to ma of spectral components. Figure 10 (left) illustrates three ated lights: CIE illuminant D65, representative of noon a fluorescent illumination that matches D65 in colour, tch these illuminants. Despite their considerable physical differences, these three spectral distributions match as isolated lights because they have the same overall balance at the level of their long-, midd e- and short-wavelength components, as detected by our combined cone and cone-opponent system. P hysically different lights that match in colour like these and plot at the same point in a chromaticity diagram are said to be metameric*. and plot at the same point in a chromaticity diagram are said to be metameric’. These three lights that match daylight all plot at the point D65 near the middle of the triangle, while positions displaced from this point signify an overall bias relative to daylight in a circuit of directions towards long, middle, short or long and short wavelengths. The direction of displacement from a giver white is specified as the dominant wavelength** if it is towards the spectral locus and as the complementary wavelength if it is towards the line of purples. The amount of displacement can be specified by the excitation purity’, the ratio of the distances from the given white to the chromaticity and to the spectral locus or line of purples. These colorimetric correlatives of hue and saturatior respectively very closely recall those Newton described in his colour circle (Figure 2; Figure 10, right). These three lights that match daylight all plot at the point D65 near the middle of the triangle, while
Figure 10: Three spectral power distributions, after [6], having the same overall balance at the level of their long-, middle-, and short-wavelength components from the point of view of the human visual system, and thus matching in colour (appearing white as an isolated light), and plotting at the same point (O) in the CIE 1931 x,} chromaticity diagram. Compare concepts of dominant wavelength and purity to Newton’s predictors of hue and saturation. The CIE x,y diagram is not the latest but is still the most familiar descendent of Newton’s colour circle. Location in the x,y chromaticity diagram represents the overall balance of wavelengths in a light at the level of its long-, middle- and short-wav: a mathematically defined “standard” human elength components, as detected by the visual system of observer. As was already implicit in Newton’s circle, physically different mixtures of spectral components can evoke the same perceived colour if they have the same “center of gravity”, or overall balance spectral distributions that appear white as iso daylight, CIE illuminant F7, representative of and a specific white LED screen adjusted to ma of spectral components. Figure 10 (left) illustrates three ated lights: CIE illuminant D65, representative of noon a fluorescent illumination that matches D65 in colour, tch these illuminants. Despite their considerable physical differences, these three spectral distributions match as isolated lights because they have the same overall balance at the level of their long-, midd e- and short-wavelength components, as detected by our combined cone and cone-opponent system. P hysically different lights that match in colour like these and plot at the same point in a chromaticity diagram are said to be metameric*. and plot at the same point in a chromaticity diagram are said to be metameric’. These three lights that match daylight all plot at the point D65 near the middle of the triangle, while positions displaced from this point signify an overall bias relative to daylight in a circuit of directions towards long, middle, short or long and short wavelengths. The direction of displacement from a giver white is specified as the dominant wavelength** if it is towards the spectral locus and as the complementary wavelength if it is towards the line of purples. The amount of displacement can be specified by the excitation purity’, the ratio of the distances from the given white to the chromaticity and to the spectral locus or line of purples. These colorimetric correlatives of hue and saturatior respectively very closely recall those Newton described in his colour circle (Figure 2; Figure 10, right). These three lights that match daylight all plot at the point D65 near the middle of the triangle, while
Figure 12: Left: Extract from the tables of Munsell notations expressed as CIE xyY values, from the 1943 Munsell renotation [18]. Right: Digital colours of Munsell value 5 (above, exported from the Virtual Colour Atlas [19]), below, plotted on a CIE x,y chromaticity diagram and in xyY colour space, using the program Artists’ Helper [20]. Figure 12 (right) shows the varying chromaticity and fixed relative luminance of a set of digite Munsell swatches of Munsell value 5 in xyY space. Even from this diagram it can be seen that xyY spac does not arrange the swatches in the regular concentric circles of equal chroma and radiating lines o equal hue that they occupy in the Munsell system. In 1976 the CIE developed two colour spaces intende to be more perceptually uniform, CIE L*a*b* and CIE L*u*v*. These transform xyY specifications int arrangements resembling (though not identical to) their arrangement in the Munsell colour solid, whic! in turn permits these specifications to be converted to correlatives of hue, lightness and chroma. CI L*a*b* is familiar to photographers and digital painters as the “Lab” space in Adobe Photoshop, and i a more convenient framework in the digital environment than the Munsell system because L*a*b values can be obtained from RGB coordinates by direct calculation rather than by the much mor computationally intensive process of interpolating values in a table.
Figure 12: Left: Extract from the tables of Munsell notations expressed as CIE xyY values, from the 1943 Munsell renotation [18]. Right: Digital colours of Munsell value 5 (above, exported from the Virtual Colour Atlas [19]), below, plotted on a CIE x,y chromaticity diagram and in xyY colour space, using the program Artists’ Helper [20]. Figure 12 (right) shows the varying chromaticity and fixed relative luminance of a set of digite Munsell swatches of Munsell value 5 in xyY space. Even from this diagram it can be seen that xyY spac does not arrange the swatches in the regular concentric circles of equal chroma and radiating lines o equal hue that they occupy in the Munsell system. In 1976 the CIE developed two colour spaces intende to be more perceptually uniform, CIE L*a*b* and CIE L*u*v*. These transform xyY specifications int arrangements resembling (though not identical to) their arrangement in the Munsell colour solid, whic! in turn permits these specifications to be converted to correlatives of hue, lightness and chroma. CI L*a*b* is familiar to photographers and digital painters as the “Lab” space in Adobe Photoshop, and i a more convenient framework in the digital environment than the Munsell system because L*a*b values can be obtained from RGB coordinates by direct calculation rather than by the much mor computationally intensive process of interpolating values in a table.
Figure 13: “White” as a colour of an isolated light (a perceived colour designation) is the way in which we perceive a spectral power distribution’s overall balance, a human-perceiver-dependent property represented by its colorimetric specification (a psychophysical colour designation). This perceivable property may be shared by many physically different spectral power distributions. In the ontological position known as physicalism these individual spectral power distributions are called “colours”; this usage is not supported by the scientific consensus embodied in the CIE ILV and does not correspond to any sense of the word “colour” defined therein. theories accept the scientific view that colour perceptions arise within the visual system but differ among themselves in part over what the word “colour” is taken to apply to. In eliminativism the word “colour” is taken to apply exclusively to colour perceptions (red, blue etc), leading to such statements as “colours do not exist”, meaning that they do not exist outside the mind. Adverbial formulations such as [21] better acknowledge the connection between colour perceptions and the stimuli that usually evoke them, for example leading to such statements as that we perceive a certain stimulus “bluely” or, I think more naturally, that the colour blue is the way in which we perceive the stimulus. In other widely held theories, the word “colour” is taken to apply to the power or disposition of lights and objects to cause perceptions of red, blue etc. (dispositionalism), or to cause such perceptions in a given perceiver and environment (relationalism). Colour physicalism on the other hand applies the word “colour” to the spectral reflectance of an object, relegating red, blue etc to being merely the appearance of this actual, physical colour. For a clear and concise account of these and other positions on the ontology of colour see [22]. the spectral reflectance of an object, relegating red, blue etc to being merely the appearance of this
Figure 13: “White” as a colour of an isolated light (a perceived colour designation) is the way in which we perceive a spectral power distribution’s overall balance, a human-perceiver-dependent property represented by its colorimetric specification (a psychophysical colour designation). This perceivable property may be shared by many physically different spectral power distributions. In the ontological position known as physicalism these individual spectral power distributions are called “colours”; this usage is not supported by the scientific consensus embodied in the CIE ILV and does not correspond to any sense of the word “colour” defined therein. theories accept the scientific view that colour perceptions arise within the visual system but differ among themselves in part over what the word “colour” is taken to apply to. In eliminativism the word “colour” is taken to apply exclusively to colour perceptions (red, blue etc), leading to such statements as “colours do not exist”, meaning that they do not exist outside the mind. Adverbial formulations such as [21] better acknowledge the connection between colour perceptions and the stimuli that usually evoke them, for example leading to such statements as that we perceive a certain stimulus “bluely” or, I think more naturally, that the colour blue is the way in which we perceive the stimulus. In other widely held theories, the word “colour” is taken to apply to the power or disposition of lights and objects to cause perceptions of red, blue etc. (dispositionalism), or to cause such perceptions in a given perceiver and environment (relationalism). Colour physicalism on the other hand applies the word “colour” to the spectral reflectance of an object, relegating red, blue etc to being merely the appearance of this actual, physical colour. For a clear and concise account of these and other positions on the ontology of colour see [22]. the spectral reflectance of an object, relegating red, blue etc to being merely the appearance of this
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Colour ScienceColour VisionColor PerceptionColour and LightColor VisionColour TermsColor ScienceColor OntologyColour EducationColor Education
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