Mark D. Fairchild, Rochester Institute of Technology, USADr. Fairchild is Professor of Color Science and Imaging Science at RIT. He is an Associate Dean for Research & Graduate Education of RIT's College of Science, facilitating the growth and strengthening of the college's research activities and graduate programs. Until recently, he had been the Director of the Munsell Color Science Laboratory for the past 12 years.

• Series Preface xiii Preface xvAcknowledgments xviiiIntroduction xix1 Human Color Vision 11.1 Optics of the Eye 21.2 The Retina 71.3 Visual Signal Processing 141.4 Mechanisms of Color Vision 191.5 Spatial and Temporal Properties of Color Vision 271.6 Color Vision Deficiencies 321.7 Key Features for Color Appearance Modeling 362 Psychophysics 382.1 Psychophysics Defined 392.2 Historical Context 402.3 Hierarchy of Scales 432.4 Threshold Techniques 452.5 Matching Techniques 492.6 One-Dimensional Scaling 502.7 Multidimensional Scaling 522.8 Design of Psychophysical Experiments 542.9 Importance in Color Appearance Modeling 553 Colorimetry 563.1 Basic and Advanced Colorimetry 573.2 Why is Color? 573.3 Light Sources and Illuminants 593.4 Colored Materials 633.5 The Human Visual Response 683.6 Tristimulus Values and Color Matching Functions 703.7 Chromaticity Diagrams 773.8 Cie Color Spaces 793.9 Color Difference Specification 813.10 The Next Step 834 Color Appearance Terminology 854.1 Importance of Definitions 854.2 Color 864.3 Hue 884.4 Brightness and Lightness 884.5 Colorfulness and Chroma 904.6 Saturation 914.7 Unrelated and Related Colors 914.8 Definitions in Equations 924.9 Brightness–Colorfulness Vs Lightness–Chroma 945 Color Order Systems 975.1 Overview and Requirements 985.2 The Munsell Book of Color 995.3 The Swedish Ncs 1045.4 The Colorcurve System 1065.5 Other Color Order Systems 1075.6 Uses of Color Order Systems 1095.7 Color Naming Systems 1126 Color Appearance Phenomena 1156.1 What are Color Appearance Phenomena? 1156.2 Simultaneous Contrast, Crispening, and Spreading 1166.3 Bezold–Brücke Hue Shift (Hue Changes with Luminance) 1206.4 Abney Effect (Hue Changes with Colorimetric Purity) 1216.5 Helmholtz–Kohlrausch Effect (BrightnessDepends On Luminance and Chromaticity) 1236.6 Hunt Effect (Colorfulness Increaseswith Luminance) 1256.7 Stevens Effect (Contrast Increaseswith Luminance) 1276.8 Helson–Judd Effect (Hue of Non-Selective Samples) 1296.9 Bartleson–Breneman Equations (ImageContrast Changes with Surround) 1316.10 Discounting-the-Illuminant 1326.11 Other Context, Structural, andPsychological Effects 1336.12 Color Constancy? 1407 Viewing Conditions 1427.1 Configuration of the Viewing Field 1427.2 Colorimetric Specification of the Viewing Field 1467.3 Modes of Viewing 1497.4 Unrelated and Related Colors Revisited 1548 Chromatic Adaptation 1568.1 Light, Dark, and Chromatic Adaptation 1578.2 Physiology 1598.3 Sensory and Cognitive Mechanisms 1708.4 Corresponding Colors Data 1748.5 Models 1778.6 Color Inconstancy Index 1788.7 Computational Color Constancy 1799 Chromatic Adaptation Models 1819.1 Von Kries Model 1829.2 Retinex Theory 1869.3 Nayatani et al. Model 1879.4 Guth’s Model 1909.5 Fairchild’s 1990 Model 1929.6 Herding Cats 1969.7 Cat02 19710 Color Appearance Models 19910.1 Definition of Color Appearance Models 19910.2 Construction of Color Appearance Models 20010.3 Cielab 20110.4 Why Not Use Just Cielab? 21010.5 What About Cieluv? 21011 The Nayatani et al. Model 21311.1 Objectives and Approach 21311.2 Input Data 21411.3 Adaptation Model 21511.4 Opponent Color Dimensions 21711.5 Brightness 21811.6 Lightness 21911.7 Hue 21911.8 Saturation 22011.9 Chroma 22111.10 Colorfulness 22111.11 Inverse Model 22211.12 Phenomena Predicted 22211.13 Why Not Use Just the Nayatani et al. Model? 22312 The Hunt Model 22512.1 Objectives and Approach 22512.2 Input Data 22612.3 Adaptation Model 22812.4 Opponent Color Dimensions 23312.5 Hue 23412.6 Saturation 23512.7 Brightness 23612.8 Lightness 23812.9 Chroma 23812.10 Colorfulness 23812.11 Inverse Model 23912.12 Phenomena Predicted 24112.13 Why Not Use Just the Hunt Model? 24213 The Rlab Model 24313.1 Objectives and Approach 24313.2 Input Data 24513.3 Adaptation Model 24613.4 Opponent Color Dimensions 24813.5 Lightness 25013.6 Hue 25013.7 Chroma 25213.8 Saturation 25213.9 Inverse Model 25213.10 Phenomena Predicted 25413.11 Why Not Use Just the Rlab Model? 25414 Other Models 25614.1 Overview 25614.2 Atd Model 25714.3 Llab Model 26414.4 Ipt Color Space 27115 The Cie Color Appearance Model (1997), Ciecam97s 27315.1 Historical Development, Objectives, and Approach 27315.2 Input Data 27615.3 Adaptation Model 27715.4 Appearance Correlates 27915.5 Inverse Model 28015.6 Phenomena Predicted 28115.7 The Zlab Color Appearance Model 28215.8 Why Not Use Just Ciecam97s? 28516 Ciecam02 28716.1 Objectives and Approach 28716.2 Input Data 28816.3 Adaptation Model 29016.4 Opponent Color Dimensions 29416.5 Hue 29416.6 Lightness 29516.7 Brightness 29516.8 Chroma 29516.9 Colorfulness 296contents xi16.10 Saturation 29616.11 Cartesian Coordinates 29616.12 Inverse Model 29716.13 Implementation Guidelines 29716.14 Phenomena Predicted 29816.15 Computational Issues 29816.16 Cam02-Ucs 30016.17 Why Not Use Just Ciecam02? 30116.18 Outlook 30117 Testing Color Appearance Models 30317.1 Overview 30317.2 Qualitative Tests 30417.3 Corresponding-Colors Data 30817.4 Magnitude Estimation Experiments 31017.5 Direct Model Tests 31217.6 Colorfulness in Projected Images 31617.7 Munsell in Color Appearance Spaces 31717.8 Cie Activities 31817.9 A Pictorial Review of Color Appearance Models 32318 Traditional Colorimetric Applications 32818.1 Color Rendering 32818.2 Color Differences 33318.3 Indices of Metamerism 33518.4 A General System of Colorimetry? 33718.5 What About Observer Metamerism? 33819 Device-Independent Color Imaging 34119.1 The Problem 34219.2 Levels of Color Reproduction 34319.3 A Revised Set of Objectives 34519.4 General Solution 34819.5 Device Calibration and Characterization 34919.6 The Need for Color Appearance Models 35419.7 Definition of Viewing Conditions 35519.8 Viewing-Conditions-IndependentColor Space 35719.9 Gamut Mapping 35719.10 Color Preferences 36119.11 Inverse Process 36219.12 Example System 36319.13 Icc Implementation 36420 I mage Appearance Modeling and the Future 36920.1 From Color Appearance to Image Appearance 37020.2 S-Cielab 37520.3 The icam Framework 37620.4 A Modular Image Difference Model 38220.5 Image Appearance and Rendering Applications 38520.6 Image Difference and Quality Applications 39120.7 icam06 39220.8 Orthogonal Color Space 39320.9 Future Directions 39621 High-Dynamic-Range Color Space 39921.1 Luminance Dynamic Range 40021.2 The Hdr Photographic Survey 40121.3 Lightness–Brightness Beyond Diffuse White 40321.4 hdr-Cielab 40421.5 hdr-Ipt 40621.6 Evans, G0, and Brilliance 40721.7 The Nayatani Theoretical Color Space 40921.8 A New Kind of Appearance Space 40921.9 Future Directions 416References 418Index 440