Dr Ján Morovi , Hewlett-Packard Espanola, S. L, Avda. Grealls, Barcelona, SpainJán Morovi is currently a Senior Color Scientist at Hewlett-Packard Espanola, Barcelona, Spain. He is highly regarded in the field of colour science, being Chair of the CIE (International Commission on Illumination) technical committee 8-03 on gamut mapping, a post he has held since 1998. Before his appointment in industry for Hewlett-Packard, Dr Morovi has also had academic experience at the University of Derby, UK. He has delivered lectures to an international audience, both academic and industrial, led industrially funded projects, and developed new commercial technologies. In addition, he has authored 62 academic publications, including book chapters, journal, and conference papers on colour gamut mapping, and also helped to create a CIE technical report detailing guidelines for the Evaluation of Mapping Algorithms.

• Foreword ixSeries Preface xiPreface xiii1. Introduction 11.1 What is Color Gamut Mapping? 11.2 Historical Context of Gamut Mapping 51.3 Who is this Book for? 71.4 What is in the Rest of the Book? 82. Basics of Color Science 112.1 What is Color? 112.2 Describing Color Experiences 122.3 The Color Ecosystem 162.4 The Human Visual System 172.5 Physical Color-related Properties 212.6 Colorimetry 252.7 Color Ecosystem Interactions 292.8 Digital Color Capture and Generation 352.9 Color Management 392.10 What can Affect the Appearance of a Pair of Stimuli? 412.11 Summary 423. Desired Color Reproduction Properties and their Evaluation 453.1 Color Reproduction Framework 453.2 Desired Color Reproduction Properties 473.3 Evaluating Reproductions 533.4 Case Study: Evaluating Printed Reproductions of a Displayed Image 703.5 Summary 714. Color Reproduction Data Flows 734.1 Device Color Spaces 734.2 Conceptual Stages of Color Reproduction 764.3 Closed-loop Color Management 814.4 sRGB Color Management 834.5 ICC Color Management 854.6 Windows Color System Color Management 884.7 Importance of Gamut Mapping in Color Reproduction 894.8 Summary 905. Overview of Gamut Mapping 915.1 Definitions 915.2 Aims of Gamut Mapping 945.3 Gamut Mapping Algorithm Context 955.4 Types of Gamut Mapping 965.5 Building Blocks of Gamut Mapping Algorithms 975.6 Factors Affecting Gamut Mapping 1055.7 Will Gamut Mapping become Redundant? 1076. Color Spaces for Gamut Mapping 1116.1 Implications of Mapping Appearance Predictors 1126.2 Which Appearance Attributes' Predictors to Map 1146.3 Overview of Color Appearance Spaces 1156.4 Mapping in Nonappearance Spaces 1196.5 Choosing a Space for Gamut Mapping 1217. Basic Computational Geometry for Gamut Mapping 1237.1 Spaces, Points, Lines and Planes 1237.2 Intersections 1267.3 Is a Point Inside or Not? 1287.4 Normals 1297.5 Triangulation 1317.6 Summary 1328. Color Gamuts and their Computation 1338.1 Challenges and Implications of Definition 1348.2 Gamut Boundary Descriptor Algorithms 1438.3 Evaluating and Operating on Gamut Boundary Descriptors 1558.4 Examples of Salient Color Gamuts 1608.5 Image Gamuts 1678.6 Summary 1699. A Case Study: Minimum Color Difference Gamut Clipping 1719.1 The Original 1719.2 The Destination Gamut 1759.3 Minimum Color Difference Gamut Mapping 1769.4 The Destination Image 1829.5 Effect of Alternatives 1839.6 Summary 19110. Survey of Gamut Mapping Algorithms 19310.1 Color-by-color Reduction 19410.2 Color-by-color Expansion 22010.3 Spatial Gamut Reduction 22410.4 Spectral Gamut Mapping 23410.5 Gamut Mapping for Special Applications 23710.6 Summary 23911. Gamut Mapping Algorithms and Color Management Systems 24111.1 Gamut Mapping Algorithms for Closed-loop Color Management 24111.2 Gamut Mapping Algorithms for sRGB Color Management 24211.3 Gamut Mapping Algorithms for ICC Color Management 24211.4 Gamut Mapping Algorithms for WCS Color Management 24411.5 Types of Color Management Context 24511.6 Spatial and Spectral Gamut Mapping 24611.7 Conclusions 24612. Evaluating Gamut Mapping Algorithms 24712.1 Why is there no Reference Data Set in Gamut Mapping Algorithm Evaluation? 24812.2 Characteristics of Published Gamut Mapping Algorithm Evaluation 25012.3 What can be Said on the Basis of Existing Evaluation Results? 25212.4 CIE Guidelines 25312.5 Studying Specific Properties of Gamut Mapping Algorithms 25512.6 Summary 25813. Conclusions 261References 265Index 281

“Jan Morovic does a good job of describing the many aspects of color. The first four chapters are expansive. They present summaries of the definition of color, basic color science, categories of possible color reproduction goals, and color mapping goals.” (COLOR research and application, June 2009)

Dr Ján Morovi , Hewlett-Packard Espanola, S. L, Avda. Grealls, Barcelona, SpainJán Morovi is currently a Senior Color Scientist at Hewlett-Packard Espanola, Barcelona, Spain. He is highly regarded in the field of colour science, being Chair of the CIE (International Commission on Illumination) technical committee 8-03 on gamut mapping, a post he has held since 1998. Before his appointment in industry for Hewlett-Packard, Dr Morovi has also had academic experience at the University of Derby, UK. He has delivered lectures to an international audience, both academic and industrial, led industrially funded projects, and developed new commercial technologies. In addition, he has authored 62 academic publications, including book chapters, journal, and conference papers on colour gamut mapping, and also helped to create a CIE technical report detailing guidelines for the Evaluation of Mapping Algorithms.

• Foreword ixSeries Preface xiPreface xiii1. Introduction 11.1 What is Color Gamut Mapping? 11.2 Historical Context of Gamut Mapping 51.3 Who is this Book for? 71.4 What is in the Rest of the Book? 82. Basics of Color Science 112.1 What is Color? 112.2 Describing Color Experiences 122.3 The Color Ecosystem 162.4 The Human Visual System 172.5 Physical Color-related Properties 212.6 Colorimetry 252.7 Color Ecosystem Interactions 292.8 Digital Color Capture and Generation 352.9 Color Management 392.10 What can Affect the Appearance of a Pair of Stimuli? 412.11 Summary 423. Desired Color Reproduction Properties and their Evaluation 453.1 Color Reproduction Framework 453.2 Desired Color Reproduction Properties 473.3 Evaluating Reproductions 533.4 Case Study: Evaluating Printed Reproductions of a Displayed Image 703.5 Summary 714. Color Reproduction Data Flows 734.1 Device Color Spaces 734.2 Conceptual Stages of Color Reproduction 764.3 Closed-loop Color Management 814.4 sRGB Color Management 834.5 ICC Color Management 854.6 Windows Color System Color Management 884.7 Importance of Gamut Mapping in Color Reproduction 894.8 Summary 905. Overview of Gamut Mapping 915.1 Definitions 915.2 Aims of Gamut Mapping 945.3 Gamut Mapping Algorithm Context 955.4 Types of Gamut Mapping 965.5 Building Blocks of Gamut Mapping Algorithms 975.6 Factors Affecting Gamut Mapping 1055.7 Will Gamut Mapping become Redundant? 1076. Color Spaces for Gamut Mapping 1116.1 Implications of Mapping Appearance Predictors 1126.2 Which Appearance Attributes' Predictors to Map 1146.3 Overview of Color Appearance Spaces 1156.4 Mapping in Nonappearance Spaces 1196.5 Choosing a Space for Gamut Mapping 1217. Basic Computational Geometry for Gamut Mapping 1237.1 Spaces, Points, Lines and Planes 1237.2 Intersections 1267.3 Is a Point Inside or Not? 1287.4 Normals 1297.5 Triangulation 1317.6 Summary 1328. Color Gamuts and their Computation 1338.1 Challenges and Implications of Definition 1348.2 Gamut Boundary Descriptor Algorithms 1438.3 Evaluating and Operating on Gamut Boundary Descriptors 1558.4 Examples of Salient Color Gamuts 1608.5 Image Gamuts 1678.6 Summary 1699. A Case Study: Minimum Color Difference Gamut Clipping 1719.1 The Original 1719.2 The Destination Gamut 1759.3 Minimum Color Difference Gamut Mapping 1769.4 The Destination Image 1829.5 Effect of Alternatives 1839.6 Summary 19110. Survey of Gamut Mapping Algorithms 19310.1 Color-by-color Reduction 19410.2 Color-by-color Expansion 22010.3 Spatial Gamut Reduction 22410.4 Spectral Gamut Mapping 23410.5 Gamut Mapping for Special Applications 23710.6 Summary 23911. Gamut Mapping Algorithms and Color Management Systems 24111.1 Gamut Mapping Algorithms for Closed-loop Color Management 24111.2 Gamut Mapping Algorithms for sRGB Color Management 24211.3 Gamut Mapping Algorithms for ICC Color Management 24211.4 Gamut Mapping Algorithms for WCS Color Management 24411.5 Types of Color Management Context 24511.6 Spatial and Spectral Gamut Mapping 24611.7 Conclusions 24612. Evaluating Gamut Mapping Algorithms 24712.1 Why is there no Reference Data Set in Gamut Mapping Algorithm Evaluation? 24812.2 Characteristics of Published Gamut Mapping Algorithm Evaluation 25012.3 What can be Said on the Basis of Existing Evaluation Results? 25212.4 CIE Guidelines 25312.5 Studying Specific Properties of Gamut Mapping Algorithms 25512.6 Summary 25813. Conclusions 261References 265Index 281

“Jan Morovic does a good job of describing the many aspects of color. The first four chapters are expansive. They present summaries of the definition of color, basic color science, categories of possible color reproduction goals, and color mapping goals.” (COLOR research and application, June 2009)

Dr Ján Morovi , Hewlett-Packard Espanola, S. L, Avda. Grealls, Barcelona, SpainJán Morovi is currently a Senior Color Scientist at Hewlett-Packard Espanola, Barcelona, Spain. He is highly regarded in the field of colour science, being Chair of the CIE (International Commission on Illumination) technical committee 8-03 on gamut mapping, a post he has held since 1998. Before his appointment in industry for Hewlett-Packard, Dr Morovi has also had academic experience at the University of Derby, UK. He has delivered lectures to an international audience, both academic and industrial, led industrially funded projects, and developed new commercial technologies. In addition, he has authored 62 academic publications, including book chapters, journal, and conference papers on colour gamut mapping, and also helped to create a CIE technical report detailing guidelines for the Evaluation of Mapping Algorithms.

• Foreword ixSeries Preface xiPreface xiii1. Introduction 11.1 What is Color Gamut Mapping? 11.2 Historical Context of Gamut Mapping 51.3 Who is this Book for? 71.4 What is in the Rest of the Book? 82. Basics of Color Science 112.1 What is Color? 112.2 Describing Color Experiences 122.3 The Color Ecosystem 162.4 The Human Visual System 172.5 Physical Color-related Properties 212.6 Colorimetry 252.7 Color Ecosystem Interactions 292.8 Digital Color Capture and Generation 352.9 Color Management 392.10 What can Affect the Appearance of a Pair of Stimuli? 412.11 Summary 423. Desired Color Reproduction Properties and their Evaluation 453.1 Color Reproduction Framework 453.2 Desired Color Reproduction Properties 473.3 Evaluating Reproductions 533.4 Case Study: Evaluating Printed Reproductions of a Displayed Image 703.5 Summary 714. Color Reproduction Data Flows 734.1 Device Color Spaces 734.2 Conceptual Stages of Color Reproduction 764.3 Closed-loop Color Management 814.4 sRGB Color Management 834.5 ICC Color Management 854.6 Windows Color System Color Management 884.7 Importance of Gamut Mapping in Color Reproduction 894.8 Summary 905. Overview of Gamut Mapping 915.1 Definitions 915.2 Aims of Gamut Mapping 945.3 Gamut Mapping Algorithm Context 955.4 Types of Gamut Mapping 965.5 Building Blocks of Gamut Mapping Algorithms 975.6 Factors Affecting Gamut Mapping 1055.7 Will Gamut Mapping become Redundant? 1076. Color Spaces for Gamut Mapping 1116.1 Implications of Mapping Appearance Predictors 1126.2 Which Appearance Attributes' Predictors to Map 1146.3 Overview of Color Appearance Spaces 1156.4 Mapping in Nonappearance Spaces 1196.5 Choosing a Space for Gamut Mapping 1217. Basic Computational Geometry for Gamut Mapping 1237.1 Spaces, Points, Lines and Planes 1237.2 Intersections 1267.3 Is a Point Inside or Not? 1287.4 Normals 1297.5 Triangulation 1317.6 Summary 1328. Color Gamuts and their Computation 1338.1 Challenges and Implications of Definition 1348.2 Gamut Boundary Descriptor Algorithms 1438.3 Evaluating and Operating on Gamut Boundary Descriptors 1558.4 Examples of Salient Color Gamuts 1608.5 Image Gamuts 1678.6 Summary 1699. A Case Study: Minimum Color Difference Gamut Clipping 1719.1 The Original 1719.2 The Destination Gamut 1759.3 Minimum Color Difference Gamut Mapping 1769.4 The Destination Image 1829.5 Effect of Alternatives 1839.6 Summary 19110. Survey of Gamut Mapping Algorithms 19310.1 Color-by-color Reduction 19410.2 Color-by-color Expansion 22010.3 Spatial Gamut Reduction 22410.4 Spectral Gamut Mapping 23410.5 Gamut Mapping for Special Applications 23710.6 Summary 23911. Gamut Mapping Algorithms and Color Management Systems 24111.1 Gamut Mapping Algorithms for Closed-loop Color Management 24111.2 Gamut Mapping Algorithms for sRGB Color Management 24211.3 Gamut Mapping Algorithms for ICC Color Management 24211.4 Gamut Mapping Algorithms for WCS Color Management 24411.5 Types of Color Management Context 24511.6 Spatial and Spectral Gamut Mapping 24611.7 Conclusions 24612. Evaluating Gamut Mapping Algorithms 24712.1 Why is there no Reference Data Set in Gamut Mapping Algorithm Evaluation? 24812.2 Characteristics of Published Gamut Mapping Algorithm Evaluation 25012.3 What can be Said on the Basis of Existing Evaluation Results? 25212.4 CIE Guidelines 25312.5 Studying Specific Properties of Gamut Mapping Algorithms 25512.6 Summary 25813. Conclusions 261References 265Index 281

“Jan Morovic does a good job of describing the many aspects of color. The first four chapters are expansive. They present summaries of the definition of color, basic color science, categories of possible color reproduction goals, and color mapping goals.” (COLOR research and application, June 2009)