pigmented colorants: dependence on media and time - Cornell ...

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Figure 3.15: These graphs show how the amount of light by photoreceptors varies with the wavelength of the light. Adapted from [SB02]. lights. Let ˆr, ˆg, and ˆ b, be the spectral energy curves associated with the three lights. These lights can be of any color (red, green, and blue, for example), as long as they are perceived differently to the viewer and are not combinations of each other. Hence, each light will excite the short S, medium M, and long L wavelength-sensitive cones to differing degrees. Figure 3.16: RGB color space. Q is the color vector, and its RGB components of Q are in gray. The blue triangle illustrates the unit plane. Given these lights, we can create new colored spectra by combining them in varying intensities. Since emitted lights are an additive color system, the final spectrum of the new color will be Rˆr + Gˆg + B ˆ b, where R, G, andB are scalars 65
that range between zero and full intensity. By varying the amount of each of the three light sources, many colors can be reproduced. Zero intensity for all three values yields black, while equal full intensity (usually one) results in white. Figure 3.16 illustrates the RGB color space, where each light source is a basis vector. The color in question can be described as a vector, whose magnitude defines the intensity of the color. Feasible colors in the range of this space are defined as ˆ Q | 0 ≤{R, G, B} ≤1. Colors outside of this range can not be matched by the three light sources. Figure 3.17: RGB Color Matching Functions. The negative portion of ¯r(λ) describes the area of the visible spectrum which the three primaries are unable to match. Adapted from [G95a]. A natural question to ask is, given a particular test color, what values of R, G, and B are required to generate the same response from a viewer? This is known as the color-matching problem. If one proceeds with this experiment using each wavelength in the visible spectrum as the test color, a set of color matching functions can be obtained. Since everyone’s response is slightly different, the procedure 66
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PIGMENTED COLORANTS: DEPENDENCE ON
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ABSTRACT We present a physically ba
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Acknowledgements This work would no
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Table of Contents 1 Introduction 1
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List of Tables 2.1 Average pigment
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3.15 Photoreceptor absorption .....
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B.15 Variation of spectral reflecta
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corrode the surfaces of materials.
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Figure 1.1: Detail of the Azor-Sado
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However, since mural artwork is typ
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at a very high quality (albeit limi
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heterogeneous sum of very different
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which linseed oil derives (the most
Page 27 and 28: oration of a rigidly painted layer
Page 29 and 30: ing will hit the ground and reflect
Page 31 and 32: tion of paint tubes in 1841 and the
Page 33 and 34: Figure 2.8: Natural pigments of ant
Page 35 and 36: ecome more common recently. The Ame
Page 37 and 38: A V = O(r2 ) O(r3 ) = 1 O(r) 24 (2.
Page 39 and 40: Table 2.2: Pigment specific gravity
Page 41 and 42: provide the underlying color to a p
Page 43 and 44: though the speed of light in air is
Page 45 and 46: In general, when light travels from
Page 47 and 48: materials while lit from behind. Li
Page 49 and 50: Table 2.4: Index of refraction η f
Page 51 and 52: to completely congeal. Hence, these
Page 53 and 54: ond together to form proteins. Exam
Page 55 and 56: to its original state by any means.
Page 57 and 58: While it has been used since the 19
Page 59 and 60: organic binder found in more conven
Page 61 and 62: 3.1.1 Visible Light Spectrum Light
Page 63 and 64: Figure 3.2: Hue, brightness and sat
Page 65 and 66: measures how much light is reflecte
Page 67 and 68: Figure 3.6: Additive color mixing o
Page 69 and 70: Figure 3.9: The physical amount of
Page 71 and 72: The vascular tunic lies on the wall
Page 73 and 74: Figure 3.11: Cross section of the r
Page 75 and 76: Not all areas have the same sensiti
Page 77: identify and distinguish between va
Page 81 and 82: spectrum. This insures that the res
Page 83 and 84: Figure 3.19: Graphical representati
Page 85 and 86: X x = (X + Y + Z) Y y = (X + Y + Z)
Page 87 and 88: color into the appropriate RGB colo
Page 89 and 90: components in the image (the smalle
Page 91 and 92: haviors of subtractive mixing and i
Page 93 and 94: of perceptually equal sizes. Unfort
Page 95 and 96: enabling one to transform between t
Page 97 and 98: andwidth as converted signals are s
Page 99 and 100: Figure 3.28: Retinal ganglion recep
Page 101 and 102: example shown in Figure 3.28. Under
Page 103 and 104: Figure 3.31: The work of Josef Albe
Page 105 and 106: sensations for each trial and picke
Page 107 and 108: Chapter 4 Previous Work There is no
Page 109 and 110: different location. Subsurface scat
Page 111 and 112: describes the scattering and absorp
Page 113 and 114: only accounts for a small percentag
Page 115 and 116: σ ′ t = σa + σ ′ s and α
Page 117 and 118: 104 Figure 4.4: A model of an alaba
Page 119 and 120: effects or are too computationally
Page 121 and 122: 108 Figure 4.6: Results using Kubel
Page 123 and 124: specifying pigments works adequatel
Page 125 and 126: color representation, it is not fea
Page 127 and 128: time. A metallic surface patina is
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the system consisted of wetness and
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or darkening enables the museum per
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in front of a displayed work. Felle
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light exposure. This effect is espe
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over time. Perceptually, these hues
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The rate of change of the concentra
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over white grounds) suffer the grea
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protects the deeper remaining color
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light source. This method is used w
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chemical smog and have been identif
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Chapter 5 Preparation & Measurement
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tending transparent pigments used i
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140 Figure 5.1: Spectral reflectanc
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the requirements of the work at han
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144 Figure 5.2: Left: Magnified vie
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Table 5.2: Relevant data regarding
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historically one of the best grades
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created far too strong of a binder,
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too brittle and cracking. While wor
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154 Figure 5.4: Reflectance values
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5.1.5 Painting After the layers of
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The gray card reflected 18% of the
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160 Figure 5.8: The optical setup f
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Note that harmonics reflect at the
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Note that the calibration factors f
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Chapter 6 Experimental Results 6.1
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168 Figure 6.1: Lapis Lazuli in dif
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(such as CIE standards C, D50, orD6
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172 Table 6.2: Perceptual differenc
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174 Figure 6.3: Munsell plots of La
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and j has a saturation of red rsat,
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178 Figure 6.4: Variation of spectr
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visible spectrum are increasing at
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182 Figure 6.5: Munsell plots of La
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trying to match color ca from the p
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as it ages. This is in direct contr
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teractive viewer. In our applicatio
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190 Figure 7.1: Our simulated canva
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where n is the normal at the curren
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In summary, our implementation prov
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Chapter 8 Conclusion We have studie
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inks are beginning to find their wa
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Appendix A Derivation of K-M theory
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∆i − =(K + S) idx 202 ∆j −
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Equation A.8 is now: Rearranging yi
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and if the paint is infinitely thic
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One concatenates the layers into a
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210 Figure B.1: Cold Glauconite in
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Table B.1: Color conversions from t
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214 Figure B.4: Munsell plots of Co
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216 Figure B.5: Burnt Sienna in dif
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220 Figure B.8: Munsell plots of La
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222 Figure B.9: Red Ochre Tint in d
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226 Figure B.12: Munsell plots of C
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228 Figure B.13: Variation of spect
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230 Figure B.15: Variation of spect
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Table B.13: Color conversions of Bu
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234 Figure B.18: Munsell plots of C
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236 Figure B.20: Munsell plots of R
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References [Alb71] Josef Albers. In
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240 [GLL + 04] Michael Goesele, Hen
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242 [KM31] Paul Kubelka and Franz M
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[Rat72] Floyd Ratliff. Contour and
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