Color Quality of Semiconductor and Conventional Light Sources

Meeting the need for a reliable publication on the topic and reflecting recent breakthroughs in the field, this is a comprehensive overview of color quality of solid-state light sources (LED-OLED and laser) and conventional lamps, providing academic researchers with an in-depth review of the current state while supporting lighting professionals in understanding, evaluating and optimizing illumination in their daily work.

Auteur
Tran Quoc Khanh is University Professor and Head of the Laboratory of Lighting Technology at the TU Darmstadt in Darmstadt, Germany. He obtained his PhD degree in Lighting Engineering from the TU Ilmenau, Germany. He obtained his Degree of Lecture Qualification (Habilitation) from the same University for his thesis in Colorimetry and Color Image Processing. He gathered industrial experience as a project manager at ARRI CineTechnik in Munchen (Germany). Tran Quoc Khanh authored and co-authored numerous scientific publications and invented several patents in different domains of lighting technology.

Peter Bodrogi is senior research fellow at the Laboratory of Lighting Technology of the TU Darmstadt in Darmstadt, Germany. He obtained his PhD degree in Information Technology from the University of Pannonia. He obtained his Degree of Lecture Qualification (Habilitation) from the TU Darmstadt in 2010 for his thesis on the optimization of modern visual technologies. He co-authored numerous scientific publications and invented patents in the domains of self-luminous display technology and lighting technology.

Quang Trinh Vinh is senior research fellow at the Laboratory of Lighting Technology of the TU Darmstadt in Darmstadt, Germany. He obtained his ME Degree in regulation technology. He obtained his Dr.-Ing. degree from the TU Darmstadt in 2013. His research subject concerns the complex mathematical modeling of high-power (phosphor-converted) LEDs, including their electric, thermal and optical behavior, and their light quality and color quality. He co-authored several scientific publications and invented patents in LED lighting technology.

Contenu

Preface xi

1 Introduction 1

References 9

2 Color Appearance and Color Quality: Phenomena and Metrics 11

2.1 Color Vision 11

2.2 Colorimetry 16

2.2.1 Color-Matching Functions and Tristimulus Values 17

2.2.2 Chromaticity Diagram 19

2.2.3 Interobserver Variability of Color Vision 20

2.2.4 Important Concepts Related to the Chromaticity Diagram 21

2.2.5 MacAdam Ellipses and the u v Chromaticity Diagram 24

2.3 Color Appearance, Color Cognition 26

2.3.1 Perceived Color Attributes 26

2.3.2 Viewing Conditions, Chromatic Adaptation, and Other Phenomena 28

2.3.3 Perceived Color Differences 29

2.3.4 Cognitive Color, Memory Color, and Semantic Interpretations 29

2.4 The Subjective Impression of Color Quality and Its Different Aspects 31

2.5 Modeling of Color Appearance and Perceived Color Differences 35

2.5.1 CIELAB Color Space 36

2.5.2 The CIECAM02 Color Appearance Model 37

2.5.3 Brightness Models 41

2.5.3.1 The CIE Brightness Model 43

2.5.3.2 The Ware and Cowan Conversion Factor formula (WCCF) 44

2.5.3.3 The Berman et al. Model 44

2.5.3.4 Fotios and Levermore's Brightness Model 45

2.5.3.5 Fairchild and Pirrotta's L Model of Chromatic Lightness 45

2.5.4 Modeling of Color Difference Perception in Color Spaces 45

2.5.4.1 CIELAB Color Difference 45

2.5.4.2 CAM02-UCS Uniform Color Space and Color Difference 46

2.6 Modeling of Color Quality 48

2.6.1 Color Fidelity Indices 49

2.6.1.1 The CIE Color-Rendering Index 49

2.6.1.2 The Color Fidelity Index of the CQS Method 52

2.6.1.3 The Color Fidelity Index CRI2012 (nCRI) 53

2.6.1.4 The Color Fidelity Index Rf of the IES Method (2015) 56

2.6.1.5 RCRI 57

2.6.1.6 Summary of the Deficiencies of Color Fidelity Metrics 57

2.6.2 Color Preference Indices 57

2.6.2.1 Judd's Flattery Index 57

2.6.2.2 Gamut Area Index (GAI) in Combination with CIE Ra 58

2.6.2.3 Thornton's Color Preference Index (CPI) 58

2.6.2.4 Memory Color Rendition Index Rm or MCRI 58

2.6.2.5 The Color Preference Indices of the CQS Method (Qa, Qp) 60

2.6.3 Color Gamut Indices 61

2.6.3.1 The Color Gamut Index of the CQS Method (Qg ) 62

2.6.3.2 The Feeling of Contrast Index (FCI) 62

2.6.3.3 Xu's Color-Rendering Capacity (CRC) 62

2.6.3.4 Gamut Area Index (GAI) 62

2.6.3.5 Fotios' Cone Surface Area (CSA) Index 62

2.6.3.6 The Color Gamut Index Rg of the IES Method (2015) 62

2.6.3.7 Deficiencies of Color Gamut Metrics 63

2.6.4 Color Discrimination Indices 63

2.7 Summary 64

References 65

3 The White Point of the Light Source 71

3.1 The Location of Unique White in the Chromaticity Diagram 74

3.2 Modeling Unique White in Terms of L M and L + M S Signals 77

3.3 Interobserver Variability of White Tone Perception 78

3.4 White Tone Preference 83

3.5 The White Tone's Perceived Brightness 85

3.6 Summary and Outlook 87

References 89

4 Object Colors Spectral Reflectance, Grouping of Colored Objects, and Color Gamut Aspects 91

4.1 Introduction: Aims and Research Questions 91

4.2 Spectral Reflectance of Flowers 94

4.3 Spectral Reflectance of Skin Tones 96

4.4 Spectral Reflectance of Art Paintings 97

4.5 The Leeds Database of Object Colors 98

4.6 State-of-the-Art Sets of Test Color Samples and Their Ability to Evaluate the Color Quality of Light Sources 100

4.7 Principles of Color Grouping with Two Examples for Applications 114

4.7.1 Method 1 Application of the Theory of Signal Processing in the Classical Approach 1204.7.2 Method 2 the Application of a Visual Color Model in the Classical Approach 121

4.7.3 Method 3 the Application of Visual Color Models in the Modern Approach 121 4.7.4 First Exampl...