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Foundations of Colour Science. From Colorimetry to Perception. Edition No. 1

  • Book

  • 560 Pages
  • October 2022
  • John Wiley and Sons Ltd
  • ID: 5836313
Presents the science of colour from new perspectives and outlines results obtained from the authors’ work in the mathematical theory of colour

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.

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. - Presents a unique compilation of the author’s substantial contributions to colour science - Offers a new approach to colour perception and measurement, developing the theoretical framework used in colorimetry - Bridges the gap between colour engineering and a coherent mathematical theory of colour - Outlines mathematical foundations applicable to the colour vision of humans and animals as well as technologies equipped with artificial photosensors - Contains algorithms for solving various problems in colour science, such as the mathematical problem of describing metameric lights - Formulates all results to be accessible to non-mathematicians and colour specialists

Foundations of Colour Science: From Colorimetry to Perception 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.

Table of Contents

1 Outline for readers in a hurry 1

I Light colour 81

2 Colour stimulus space and colour mechanisms 85

2.1 Grassmann structures and Grassmann colour codes 89

2.2 Continuous Grassmann structures and continuous Grassmann colour codes 97

3 Identification of Grassmann structures based on metameric matching 101

3.1 Colourmatching functions 102

3.2 Monochromatic primaries and colour matching functions in the trichromatic case (=3) 109

3.3 Fundamental colour mechanisms in human colour vision 112

3.3.1 K¨onig’s approach to identification of the fundamental colourmechanisms 120

3.3.2 Some estimates of the cone fundamentals used in colour research and applications 123

4 Colour-signal cone 129

4.1 Strong colour-signal-cone-boundary hypothesis 133

4.2 Empirical status of the strong colour-signal-cone-boundary hypothesis 138

4.3 Colour-signal-cone-boundary hypothesis 145

4.4 The colour-signal cone of a 3-pigment Grassmann-Govardovskii structure 149

5 Colour stimulus manifold 153

5.1 Three-dimensional colour stimulusmanifold 155

5.2 Non-linear colour stimulus map Colour stimulus transformation caused by themedium 160

5.2.1 The colour stimulus shift caused by the medium variations  161

5.2.2 Colour robustness tomediumvariations 163

5.3 Causes of individual differences in trichromatic colour matching   165

5.3.1 Effect of the photopigment peak sensitivity on the-coordinates 166

5.3.2 Effect of the ocular media transmittance on -coordinates 171

5.3.3 Trade-off between the ocular media spectral transmittance and the photopigment peak sensitivity in their effect on colour 174

5.3.4 Dependence of the equivalent peak-wavelength shift on light Impossibility to overcome colour deficiency using a coloured filter 176

5.3.5 Parametric identification of fundamental colour mechanisms 180

6 Light metamerism 183

6.1 Metamer sets 184

6.2 Colour mechanisms’ transformations preserving light metamerism 188

6.3 Lightmetamerismindex 190

7 Light metamer mismatching 191

7.1 Metamer-mismatch regions 191

7.2 Indices of lightmetamer mismatching 197

7.3 Computing trichromaticmetamer-mismatch regions 202

7.3.1 Effect of the spectral positioning of photopigments onmetamer mismatching 206

7.3.2 Effect of the peak photopigment absorbance on metamer mismatching 210

7.3.3 Metamer mismatching depending on the position in the chromaticity diagram 211

7.3.4 Metamer mismatching induced by pre-receptoral filters 211

7.3.5 Differences between cone fundamentals as revealed bymetamer mismatching 217

7.3.6 Metamer mismatching for the 10◦ colour matching functions of Stiles and Burch 221

7.3.7 Metamer mismatching induced by neutral density filters  234

7.3.8 Metamer mismatching produced by camera sensors 238

8 Light-colour perception 243

8.1 Achromatic scales and achromatic codes 248

8.1.1 Ordinal brightness scales 249

8.1.2 Grassmann brightness code Luminance 254

8.2 Hue, purity, and brightness fibre bundles Cylindrical and psychophysical colour coordinates 262

8.3 Colour transformation caused by media and metamer mismatching, as expressed in the psychophysical colour coordinates 270

8.4 Light-colour perception in dichromats 273

8.5 Chromatic structures 280

8.5.1 Partial hue-matching 283

8.5.2 Experiment on partial hue-matching 289

8.5.3 Colour categories 292

8.5.4 Chromatically ordered structures 297

8.5.5 Chromatic scales and chromatic codes 299

8.5.6 Hue, purity and saturation in chromatic structures 301

8.6 Light-colour manifold 304

8.6.1 Hue cyclic order 305

8.6.2 Light-colour manifold 308

8.6.3 Circular Hering structures, their representation and experimental identification 311

8.6.4 Light-colour manifold vs colour stimulus manifold 321

9 Typology of light-colour perception Inter-individual differences 329

10 Colour matching structures and matching metamerism 341

10.1 Colourmatching structures 347

10.2 Matchingmetamerism 358

11 Identification of Grassmann structures induced by colour matching structures 363

11.1 Colour matching set, threshold set, and sensitivity function 364

11.2 Regular and strongly regular tolerance extensions 368

11.3 Identification of Grassmann structures induced by colour matching tolerance relations 371

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

11.3.2 Deriving the linear colour mechanism space from the colour matching set (the method of tangential hyperplane 378

11.3.3 Deriving the fundamental colour mechanisms from the colour matching set that they generate (the method of quadratic approximation) 383

12 Identification of indiscriminate relations Colour detection and discrimination 391

12.1 Colour detectionmodels 394

12.1.1 Single-channel detectionmodels 394

12.1.2 Fundamental colour mechanisms revisited 397

12.1.3 Multi-channel detectionmodels 399

12.2 Peak-detector model equivalent to a sublinear colour detectionmodel  400

12.2.1 Sublinear colour detectionmodels 401

12.2.2 Multi-channel sublinearmodels 402

12.2.3 Themost sensitive colour mechanisms 404

12.3 Colour discriminationmodels 409

13 In search of colour mechanisms in the eye and the brain 413

13.1 Do the cone photoreceptor responses encode the colour stimulus?  413

13.1.1 Local non-linearity of the photoreceptor response 414

13.1.2 Light adaptation in photoreceptors 415

13.1.3 Spatial interaction between the cone photoreceptors 417

13.1.4 Why the colour stimulus cannot be derived from the cone photoreceptor responses 417

13.2 Do cone-opponent neural cells encode the opponent chromatic codes? 418

13.3 Transition to a different paradigm 425

13.3.1 From symmetric to asymmetric colour matching 425

13.3.2 Fromlight stimulus to light-stimulus array 428

13.3.3 On the notion of ”neural image” 430

13.4 Spatio-chromatic processing in the visual cortex 436

13.4.1 Estimating luminance-pattern gradient using simple cortical cells 436

13.4.2 Directional gradient-encoding with double-opponent cells 446

13.4.3 Difference in spatial sensitivity of (M+L)-, (M-L)-, and S-(M+L)-cells, and its implication for colour perception 449

13.4.4 Representation of the colour-signal surface in the form of its tangent bundle 450

Object colour 458

14 Object-colour solid 465

14.1 General properties of the object-colour solid 466

14.2 Optimal object stimuli 468

14.3 Elementary step functions as optimal object stimuli 470

14.4 Optimal object stimuli for trichromatic human observers 472

14.5 Condition for all step functions of degree to be optimal object stimuli 472

15 Trichromatic regular object-colour solid 475

15.1 Meridians of the trichromatic regular object-colour solid 475

15.2 Equator of the trichromatic object-colour solid and strictly optimal object stimuli 481

16 Object-colour stimulus manifold 489

16.1 Objectmetamerism 489

16.2 Object atlas 493

16.3 Object-colour stimulus manifold Illuminant-induced nonlinear object-colour stimulusmap 496

16.4 Trichromatic object-colour stimulusmanifold 497

16.4.1 Trichromatic regular object-colour stimulus manifold and its spherical representation 497

16.4.2 Spherical representation of the trichromatic objectcolour stimulus manifold and the object-colour stimulus gamut 502

16.4.3 Object-colour stimulus shift induced by the illuminant change 504

17 Object-colour perception in a single-illuminant scene 507

17.1 Perceptual object-colour coordinates 513

17.2 Perceptual correlates of coordinates 516

17.3 Effect of illumination on object-colour in a single-illuminant scene: Object-colour shift induced by illumination 521

17.4 Object-colour perception by dichromats in a single-illuminant scene 524

18 Object metamer mismatching 535

18.1 Metamer-mismatch regions 535

18.2 Numerical evaluation ofmetamer-mismatch regions 539

18.3 Indices of objectmetamer mismatching 542

18.4 Object-metamerism-preserving transformations of colour mechanisms 545

19 Object-colour perception in a multiple-illuminant scene 549

19.1 Object/light colour equivalence and its inseparability 554

19.2 Object/light atlas 556

19.3 Object/light colour stimulusmanifold 557

19.3.1 Asymmetric colourmatching 557

19.3.2 Material colour 561

19.3.3 Lighting colour 562

19.3.4 Object/light colour stimulus manifold Material and lighting components of object/light colour stimulus manifold Material- and lighting-colour coordinates 564

19.4 Material colour shift induced by illumination change Implication for the problemof ”colour constancy” 569

20 Object-colour indeterminacy 573

20.1 Trade-off between object and light components 573

20.2 Trade-off betweenmaterial and lighting colours 579

20.2.1 Invariant relationship between lightness and lighting brightness 581

20.2.2 Invariant relationship between lightness, lighting brightness and shading brightness 586

20.2.3 Shading as a sensory basis of shape 588

20.2.4 Invariant relationship between material-colour image and lighting-colour image in the chromatic domain 590

20.3 Object-colour indeterminacy in variegated scenes Impact of articulation 591

20.4 Implication for measuring object-colour 594

21 On perception in general: An outline of an alternative approach 601

21.1 What is colour for? 603

21.2 The need for a new approach to perception: Linguistic metaphor 607

22 Epilogue 619

References 623

A Some auxiliary facts from functional analysis 649

A.1 Banach spaces of measures and functions, and stimulus spaces 649

A.2 Convex analysis 652

B Proofs 657

Authors

Alexander D. Logvinenko Glasgow Caledonian University. Vladimir L. Levin Russian Academy of Sciences.