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

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The Kubelka-Munk equations were generalized to allow arbitrary mixtures of pigments [Dun40]. If there are n multiple materials in the same layer with different scattering and absorption coefficients (ie: multiple pigments within the same layer of paint), they may be combined via linear weighting using their respective concentrations ci: Smixture(λ) = Kmixture(λ) = n ciSi(λ) i=1 205 n ciKi(λ) (A.16) Kubelka extended the 1931 work in two subsequent articles. He first solved the differential equations of Equation A.4 for a finite thickness of paint (originally, the infinite case was presented) [Kub48]. If the paint film has thickness x, then Rx = i=1 1 R∞ (R0 − R∞) − R∞ R0 − 1 R∞ (R0 − R∞) − R0 − 1 R∞ 1 e Sx( R∞ −R∞) 1 e Sx( R∞ −R∞) (A.17) Another form of this equation can be found using hyperbolic functions, allowing for simpler computation: Rx = 1 − R0(a − b coth bSx) a − R0 + b coth bSx (A.18) where a =1+ K S and b = √ a 2 − 1 as earlier. When the paint becomes thick enough to hide the substrate, R0 → 0. Thus we have Rx = 1 a + b coth bSx (A.19)
and if the paint is infinitely thick, x →∞,sobSx → 1 reducing to R∞ = 1 a + b 206 (A.20) which is exactly Equation A.14, showing that the infinite-thickness solution is just a special case of the more general finite-thickness case. In the same work, Kubelka also found an analogous formula with hyperbolic terms representing transmittance T through a layer: T = b a sinh bSx + b cosh bSx (A.21) Later, Kubelka presented a simple method for computing the reflectance and transmittance of several layers composited on top of each other [Kub54]. Con- sider two homogeneous layers of different optical properties and possibly different thicknesses. As seen in Figure A.2, light entering such a material is reflected and transmitted multiple times, forming a tree-like structure for each incident ray. As the light flux from an incident ray hits the top layer, part is reflected (R1) and part is transmitted (T1). T1 reaches the bottom layer and reflects T1R2, while transmitting T1T2. The portion T1R2 hits the lower portion of the top layer and transmits T1R2T1 ′ (which exits back into the air), while reflecting T1R2R1 back into the lower layer ··· and so on, ad infinitum. Adding up the portions finally transmitted by the combined layered specimen, we have Ttotal = T1T2(1 + R1 ′R2 + R 2 1 ′R2 2 + ···)= T1T2 1 − R1 ′R2 (A.22)
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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
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oration of a rigidly painted layer
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ing will hit the ground and reflect
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tion of paint tubes in 1841 and the
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Figure 2.8: Natural pigments of ant
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ecome more common recently. The Ame
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A V = O(r2 ) O(r3 ) = 1 O(r) 24 (2.
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Table 2.2: Pigment specific gravity
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provide the underlying color to a p
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though the speed of light in air is
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In general, when light travels from
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materials while lit from behind. Li
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Table 2.4: Index of refraction η f
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to completely congeal. Hence, these
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ond together to form proteins. Exam
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to its original state by any means.
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While it has been used since the 19
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organic binder found in more conven
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3.1.1 Visible Light Spectrum Light
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Figure 3.2: Hue, brightness and sat
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measures how much light is reflecte
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Figure 3.6: Additive color mixing o
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Figure 3.9: The physical amount of
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The vascular tunic lies on the wall
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Figure 3.11: Cross section of the r
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Not all areas have the same sensiti
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identify and distinguish between va
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that range between zero and full in
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spectrum. This insures that the res
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Figure 3.19: Graphical representati
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X x = (X + Y + Z) Y y = (X + Y + Z)
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color into the appropriate RGB colo
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components in the image (the smalle
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haviors of subtractive mixing and i
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of perceptually equal sizes. Unfort
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enabling one to transform between t
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andwidth as converted signals are s
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Figure 3.28: Retinal ganglion recep
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example shown in Figure 3.28. Under
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Figure 3.31: The work of Josef Albe
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sensations for each trial and picke
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Chapter 4 Previous Work There is no
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different location. Subsurface scat
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describes the scattering and absorp
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only accounts for a small percentag
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σ ′ t = σa + σ ′ s and α
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104 Figure 4.4: A model of an alaba
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effects or are too computationally
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108 Figure 4.6: Results using Kubel
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specifying pigments works adequatel
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color representation, it is not fea
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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
Page 167 and 168: 154 Figure 5.4: Reflectance values
Page 169 and 170: 5.1.5 Painting After the layers of
Page 171 and 172: The gray card reflected 18% of the
Page 173 and 174: 160 Figure 5.8: The optical setup f
Page 175 and 176: Note that harmonics reflect at the
Page 177 and 178: Note that the calibration factors f
Page 179 and 180: Chapter 6 Experimental Results 6.1
Page 181 and 182: 168 Figure 6.1: Lapis Lazuli in dif
Page 183 and 184: (such as CIE standards C, D50, orD6
Page 185 and 186: 172 Table 6.2: Perceptual differenc
Page 187 and 188: 174 Figure 6.3: Munsell plots of La
Page 189 and 190: and j has a saturation of red rsat,
Page 191 and 192: 178 Figure 6.4: Variation of spectr
Page 193 and 194: visible spectrum are increasing at
Page 195 and 196: 182 Figure 6.5: Munsell plots of La
Page 197 and 198: trying to match color ca from the p
Page 199 and 200: as it ages. This is in direct contr
Page 201 and 202: teractive viewer. In our applicatio
Page 203 and 204: 190 Figure 7.1: Our simulated canva
Page 205 and 206: where n is the normal at the curren
Page 207 and 208: In summary, our implementation prov
Page 209 and 210: Chapter 8 Conclusion We have studie
Page 211 and 212: inks are beginning to find their wa
Page 213 and 214: Appendix A Derivation of K-M theory
Page 215 and 216: ∆i − =(K + S) idx 202 ∆j −
Page 217: Equation A.8 is now: Rearranging yi
Page 221 and 222: One concatenates the layers into a
Page 223 and 224: 210 Figure B.1: Cold Glauconite in
Page 225 and 226: Table B.1: Color conversions from t
Page 227 and 228: 214 Figure B.4: Munsell plots of Co
Page 229 and 230: 216 Figure B.5: Burnt Sienna in dif
Page 233 and 234: 220 Figure B.8: Munsell plots of La
Page 235 and 236: 222 Figure B.9: Red Ochre Tint in d
Page 239 and 240: 226 Figure B.12: Munsell plots of C
Page 241 and 242: 228 Figure B.13: Variation of spect
Page 243 and 244: 230 Figure B.15: Variation of spect
Page 245 and 246: Table B.13: Color conversions of Bu
Page 247 and 248: 234 Figure B.18: Munsell plots of C
Page 249 and 250: 236 Figure B.20: Munsell plots of R
Page 251 and 252: References [Alb71] Josef Albers. In
Page 253 and 254: 240 [GLL + 04] Michael Goesele, Hen
Page 255 and 256: 242 [KM31] Paul Kubelka and Franz M
Page 257 and 258: [Rat72] Floyd Ratliff. Contour and
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