Details

Foundations of Colour Science


Foundations of Colour Science

From Colorimetry to Perception
1. Aufl.

von: Alexander D. Logvinenko, Vladimir L. Levin

139,99 €

Verlag: Wiley
Format: PDF
Veröffentl.: 23.09.2022
ISBN/EAN: 9781119885900
Sprache: englisch
Anzahl Seiten: 560

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Beschreibungen

<p><b>Presents the science of colour from new perspectives and outlines results obtained from the authors&rsquo; work in the mathematical theory of colour </b> <p> This innovative volume summarizes existing knowledge in the field, attempting to present as much data as possible about colour, accumulated in various branches of science (physics, phychophysics, colorimetry, physiology) from a unified theoretical position. Written by a colour specialist and a professional mathematician, the book offers a new theoretical framework based on functional analysis and convex analysis. Employing these branches of mathematics, instead of more conventional linear algebra, allows them to provide the knowledge required for developing techniques to measure colour appearance to the standards adopted in colorimetric measurements. The authors describe the mathematics in a language that is understandable for colour specialists and include a detailed overview of all chapters to help readers not familiar with colour science. <p>Divided into two parts, the book first covers various key aspects of light colour, such as colour stimulus space, colour mechanisms, colour detection and discrimination, light-colour perception typology, and light metamerism. The second part focuses on object colour, featuring detailed coverage of object-colour perception in single- and multiple-illuminant scenes, object-colour solid, colour constancy, <p> metamer mismatching, object-colour indeterminacy and more. Throughout the book, the authors combine differential geometry and topology with the scientific principles on which colour measurement and specification are currently based and applied in industrial applications. <ul> <li>Presents a unique compilation of the author&rsquo;s substantial contributions to colour science</li> <li>Offers a new approach to colour perception and measurement, developing the theoretical framework used in colorimetry</li> <li>Bridges the gap between colour engineering and a coherent mathematical theory of colour</li> <li>Outlines mathematical foundations applicable to the colour vision of humans and animals as well as technologies equipped with artificial photosensors</li> <li>Contains algorithms for solving various problems in colour science, such as the mathematical problem of describing metameric lights</li> <li>Formulates all results to be accessible to non-mathematicians and colour specialists</li></ul><p><i>Foundations of Colour Science: From Colorimetry to Perception </i>is an invaluable resource for academics, researchers, industry professionals and undergraduate and graduate students with interest in a mathematical approach to the science of colour.
<p><b>1 Outline for readers in a hurry 1</b></p> <p>I Light colour 81</p> <p><b>2 Colour stimulus space and colour mechanisms 85</b></p> <p>2.1 Grassmann structures and Grassmann colour codes 89</p> <p>2.2 Continuous Grassmann structures and continuous Grassmann colour codes 97</p> <p><b>3 Identification of Grassmann structures based on metameric matching 101</b></p> <p>3.1 Colourmatching functions 102</p> <p>3.2 Monochromatic primaries and colour matching functions in the trichromatic case (=3) 109</p> <p>3.3 Fundamental colour mechanisms in human colour vision 112</p> <p>3.3.1 K&uml;onig&rsquo;s approach to identification of the fundamental colourmechanisms 120</p> <p>3.3.2 Some estimates of the cone fundamentals used in colour research and applications 123</p> <p><b>4 Colour-signal cone 129</b></p> <p>4.1 Strong colour-signal-cone-boundary hypothesis 133</p> <p>4.2 Empirical status of the strong colour-signal-cone-boundary hypothesis 138</p> <p>4.3 Colour-signal-cone-boundary hypothesis 145</p> <p>4.4 The colour-signal cone of a 3-pigment Grassmann-Govardovskii structure 149</p> <p><b>5 Colour stimulus manifold 153</b></p> <p>5.1 Three-dimensional colour stimulusmanifold 155</p> <p>5.2 Non-linear colour stimulus map Colour stimulus transformation caused by themedium 160</p> <p>5.2.1 The colour stimulus shift caused by the medium variations &nbsp;161</p> <p>5.2.2 Colour robustness tomediumvariations 163</p> <p>5.3 Causes of individual differences in trichromatic colour matching&nbsp; &nbsp;165</p> <p>5.3.1 Effect of the photopigment peak sensitivity on the-coordinates 166</p> <p>5.3.2 Effect of the ocular media transmittance on -coordinates 171</p> <p>5.3.3 Trade-off between the ocular media spectral transmittance and the photopigment peak sensitivity in their effect on colour 174</p> <p>5.3.4 Dependence of the equivalent peak-wavelength shift on light Impossibility to overcome colour deficiency using a coloured filter 176</p> <p>5.3.5 Parametric identification of fundamental colour mechanisms 180</p> <p><b>6 Light metamerism 183</b></p> <p>6.1 Metamer sets 184</p> <p>6.2 Colour mechanisms&rsquo; transformations preserving light metamerism 188</p> <p>6.3 Lightmetamerismindex 190</p> <p><b>7 Light metamer mismatching 191</b></p> <p>7.1 Metamer-mismatch regions 191</p> <p>7.2 Indices of lightmetamer mismatching 197</p> <p>7.3 Computing trichromaticmetamer-mismatch regions 202</p> <p>7.3.1 Effect of the spectral positioning of photopigments onmetamer mismatching 206</p> <p>7.3.2 Effect of the peak photopigment absorbance on metamer mismatching 210</p> <p>7.3.3 Metamer mismatching depending on the position in the chromaticity diagram 211</p> <p>7.3.4 Metamer mismatching induced by pre-receptoral filters 211</p> <p>7.3.5 Differences between cone fundamentals as revealed bymetamer mismatching 217</p> <p>7.3.6 Metamer mismatching for the 10◦ colour matching functions of Stiles and Burch 221</p> <p>7.3.7 Metamer mismatching induced by neutral density filters &nbsp;234</p> <p>7.3.8 Metamer mismatching produced by camera sensors 238</p> <p><b>8 Light-colour perception 243</b></p> <p>8.1 Achromatic scales and achromatic codes 248</p> <p>8.1.1 Ordinal brightness scales 249</p> <p>8.1.2 Grassmann brightness code Luminance 254</p> <p>8.2 Hue, purity, and brightness fibre bundles Cylindrical and psychophysical colour coordinates 262</p> <p>8.3 Colour transformation caused by media and metamer mismatching, as expressed in the psychophysical colour coordinates 270</p> <p>8.4 Light-colour perception in dichromats 273</p> <p>8.5 Chromatic structures 280</p> <p>8.5.1 Partial hue-matching 283</p> <p>8.5.2 Experiment on partial hue-matching 289</p> <p>8.5.3 Colour categories 292</p> <p>8.5.4 Chromatically ordered structures 297</p> <p>8.5.5 Chromatic scales and chromatic codes 299</p> <p>8.5.6 Hue, purity and saturation in chromatic structures 301</p> <p>8.6 Light-colour manifold 304</p> <p>8.6.1 Hue cyclic order 305</p> <p>8.6.2 Light-colour manifold 308</p> <p>8.6.3 Circular Hering structures, their representation and experimental identification 311</p> <p>8.6.4 Light-colour manifold vs colour stimulus manifold 321</p> <p><b>9 Typology of light-colour perception Inter-individual differences 329</b></p> <p><b>10 Colour matching structures and matching metamerism 341</b></p> <p>10.1 Colourmatching structures 347</p> <p>10.2 Matchingmetamerism 358</p> <p><b>11 Identification of Grassmann structures induced by colour matching structures 363</b></p> <p>11.1 Colour matching set, threshold set, and sensitivity function 364</p> <p>11.2 Regular and strongly regular tolerance extensions 368</p> <p>11.3 Identification of Grassmann structures induced by colour matching tolerance relations 371</p> <p>11.3.1 Identification of the linear colour mechanism space as a subspace in the linear span of a given set of linearly independent functionals 372</p> <p>11.3.2 Deriving the linear colour mechanism space from the colour matching set (the method of tangential hyperplane 378</p> <p>11.3.3 Deriving the fundamental colour mechanisms from the colour matching set that they generate (the method of quadratic approximation) 383</p> <p><b>12 Identification of indiscriminate relations Colour detection and discrimination 391</b></p> <p>12.1 Colour detectionmodels 394</p> <p>12.1.1 Single-channel detectionmodels 394</p> <p>12.1.2 Fundamental colour mechanisms revisited 397</p> <p>12.1.3 Multi-channel detectionmodels 399</p> <p>12.2 Peak-detector model equivalent to a sublinear colour detectionmodel &nbsp;400</p> <p>12.2.1 Sublinear colour detectionmodels 401</p> <p>12.2.2 Multi-channel sublinearmodels 402</p> <p>12.2.3 Themost sensitive colour mechanisms 404</p> <p>12.3 Colour discriminationmodels 409</p> <p><b>13 In search of colour mechanisms in the eye and the brain 413</b></p> <p>13.1 Do the cone photoreceptor responses encode the colour stimulus? &nbsp;413</p> <p>13.1.1 Local non-linearity of the photoreceptor response 414</p> <p>13.1.2 Light adaptation in photoreceptors 415</p> <p>13.1.3 Spatial interaction between the cone photoreceptors 417</p> <p>13.1.4 Why the colour stimulus cannot be derived from the cone photoreceptor responses 417</p> <p>13.2 Do cone-opponent neural cells encode the opponent chromatic codes? 418</p> <p>13.3 Transition to a different paradigm 425</p> <p>13.3.1 From symmetric to asymmetric colour matching 425</p> <p>13.3.2 Fromlight stimulus to light-stimulus array 428</p> <p>13.3.3 On the notion of &rdquo;neural image&rdquo; 430</p> <p>13.4 Spatio-chromatic processing in the visual cortex 436</p> <p>13.4.1 Estimating luminance-pattern gradient using simple cortical cells 436</p> <p>13.4.2 Directional gradient-encoding with double-opponent cells 446</p> <p>13.4.3 Difference in spatial sensitivity of (M+L)-, (M-L)-, and S-(M+L)-cells, and its implication for colour perception 449</p> <p>13.4.4 Representation of the colour-signal surface in the form of its tangent bundle 450</p> <p>Object colour 458</p> <p><b>14 Object-colour solid 465</b></p> <p>14.1 General properties of the object-colour solid 466</p> <p>14.2 Optimal object stimuli 468</p> <p>14.3 Elementary step functions as optimal object stimuli 470</p> <p>14.4 Optimal object stimuli for trichromatic human observers 472</p> <p>14.5 Condition for all step functions of degree to be optimal object stimuli 472</p> <p><b>15 Trichromatic regular object-colour solid 475</b></p> <p>15.1 Meridians of the trichromatic regular object-colour solid 475</p> <p>15.2 Equator of the trichromatic object-colour solid and strictly optimal object stimuli 481</p> <p><b>16 Object-colour stimulus manifold 489</b></p> <p>16.1 Objectmetamerism 489</p> <p>16.2 Object atlas 493</p> <p>16.3 Object-colour stimulus manifold Illuminant-induced nonlinear object-colour stimulusmap 496</p> <p>16.4 Trichromatic object-colour stimulusmanifold 497</p> <p>16.4.1 Trichromatic regular object-colour stimulus manifold and its spherical representation 497</p> <p>16.4.2 Spherical representation of the trichromatic objectcolour stimulus manifold and the object-colour stimulus gamut 502</p> <p>16.4.3 Object-colour stimulus shift induced by the illuminant change 504</p> <p><b>17 Object-colour perception in a single-illuminant scene 507</b></p> <p>17.1 Perceptual object-colour coordinates 513</p> <p>17.2 Perceptual correlates of coordinates 516</p> <p>17.3 Effect of illumination on object-colour in a single-illuminant scene: Object-colour shift induced by illumination 521</p> <p>17.4 Object-colour perception by dichromats in a single-illuminant scene 524</p> <p><b>18 Object metamer mismatching 535</b></p> <p>18.1 Metamer-mismatch regions 535</p> <p>18.2 Numerical evaluation ofmetamer-mismatch regions 539</p> <p>18.3 Indices of objectmetamer mismatching 542</p> <p>18.4 Object-metamerism-preserving transformations of colour mechanisms 545</p> <p><b>19 Object-colour perception in a multiple-illuminant scene 549</b></p> <p>19.1 Object/light colour equivalence and its inseparability 554</p> <p>19.2 Object/light atlas 556</p> <p>19.3 Object/light colour stimulusmanifold 557</p> <p>19.3.1 Asymmetric colourmatching 557</p> <p>19.3.2 Material colour 561</p> <p>19.3.3 Lighting colour 562</p> <p>19.3.4 Object/light colour stimulus manifold Material and lighting components of object/light colour stimulus manifold Material- and lighting-colour coordinates 564</p> <p>19.4 Material colour shift induced by illumination change Implication for the problemof &rdquo;colour constancy&rdquo; 569</p> <p><b>20 Object-colour indeterminacy 573</b></p> <p>20.1 Trade-off between object and light components 573</p> <p>20.2 Trade-off betweenmaterial and lighting colours 579</p> <p>20.2.1 Invariant relationship between lightness and lighting brightness 581</p> <p>20.2.2 Invariant relationship between lightness, lighting brightness and shading brightness 586</p> <p>20.2.3 Shading as a sensory basis of shape 588</p> <p>20.2.4 Invariant relationship between material-colour image and lighting-colour image in the chromatic domain 590</p> <p>20.3 Object-colour indeterminacy in variegated scenes Impact of articulation 591</p> <p>20.4 Implication for measuring object-colour 594</p> <p><b>21 On perception in general: An outline of an alternative approach 601</b></p> <p>21.1 What is colour for? 603</p> <p>21.2 The need for a new approach to perception: Linguistic metaphor 607</p> <p>22 Epilogue 619</p> <p>References 623</p> <p>A Some auxiliary facts from functional analysis 649</p> <p>A.1 Banach spaces of measures and functions, and stimulus spaces 649</p> <p>A.2 Convex analysis 652</p> <p>B Proofs 657</p>
<p><b>Alexander D. Logvinenko</b> is a Professor of Vision Science at Glasgow Caledonian University. His research interests deal with visual perception, psychophysics, and colour vision, with an emphasis on the application of mathematical methods to the vision sciences. For the last 25 years, he has been working on colour and human perception of colour. <p><b>Vladimir L. Levin</b> was a Professor of Mathematics at the Russian Academy of Sciences. Now deceased, Dr Levin’s fields of interest included functional analysis, convex analysis of extremal problems, and set-valued analysis. He was awarded the Nemchinov Prize of the Russian Academy of Sciences in 2008.
<p><b>Presents the science of colour from new perspectives and outlines results obtained from the authors’ work in the mathematical theory of colour</b> <p>This innovative volume summarizes existing knowledge in the field, attempting to present as much data as possible about colour, accumulated in various branches of science (physics, phychophysics, colorimetry, physiology) from a unified theoretical position. Written by a colour specialist and a professional mathematician, the book offers a new theoretical framework based on functional analysis and convex analysis. Employing these branches of mathematics, instead of more conventional linear algebra, allows them to provide the knowledge required for developing techniques to measure colour appearance to the standards adopted in colorimetric measurements. The authors describe the mathematics in a language that is understandable for colour specialists and include a detailed overview of all chapters to help readers not familiar with colour science. <p>Divided into two parts, the book first covers various key aspects of light colour, such as colour stimulus space, colour mechanisms, colour detection and discrimination, light-colour perception typology, and light metamerism. The second part focuses on object colour, featuring detailed coverage of object-colour perception in single- and multiple-illuminant scenes, object-colour solid, colour constancy, metamer mismatching, object-colour indeterminacy and more. Throughout the book, the authors combine differential geometry and topology with the scientific principles on which colour measurement and specification are currently based and applied in industrial applications. <ul><li>Presents a unique compilation of the author’s substantial contributions to colour science</li> <li>Offers a new approach to colour perception and measurement, developing the theoretical framework used in colorimetry</li> <li>Bridges the gap between colour engineering and a coherent mathematical theory of colour</li> <li>Outlines mathematical foundations applicable to the colour vision of humans and animals as well as technologies equipped with artificial photosensors</li> <li>Contains algorithms for solving various problems in colour science, such as the mathematical problem of describing metameric lights</li> <li>Formulates all results to be accessible to non-mathematicians and colour specialists</li></ul> <p><i>Foundations of Colour Science: From Colorimetry to Perception</i> is an invaluable resource for academics, researchers, industry professionals and undergraduate and graduate students with interest in a mathematical approach to the science of colour.

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