Color Quality of Semiconductor and Conventional Light Sources (eBook)

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 München (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.

Cover 1
Title Page 5
Copyright 6
Contents 7
Preface 13
Chapter 1 Introduction 15
References 23
Chapter 2 Color Appearance and Color Quality: Phenomena and Metrics 25
2.1 Color Vision 25
2.2 Colorimetry 30
2.2.1 Color-Matching Functions and Tristimulus Values 31
2.2.2 Chromaticity Diagram 33
2.2.3 Interobserver Variability of Color Vision 34
2.2.4 Important Concepts Related to the Chromaticity Diagram 35
2.2.5 MacAdam Ellipses and the u? ? v? Chromaticity Diagram 38
2.3 Color Appearance, Color Cognition 40
2.3.1 Perceived Color Attributes 40
2.3.2 Viewing Conditions, Chromatic Adaptation, and Other Phenomena 42
2.3.3 Perceived Color Differences 43
2.3.4 Cognitive Color, Memory Color, and Semantic Interpretations 43
2.4 The Subjective Impression of Color Quality and Its Different Aspects 45
2.5 Modeling of Color Appearance and Perceived Color Differences 49
2.5.1 CIELAB Color Space 50
2.5.2 The CIECAM02 Color Appearance Model 51
2.5.3 Brightness Models 55
2.5.4 Modeling of Color Difference Perception in Color Spaces 59
2.6 Modeling of Color Quality 62
2.6.1 Color Fidelity Indices 63
2.6.2 Color Preference Indices 71
2.6.3 Color Gamut Indices 75
2.6.4 Color Discrimination Indices 77
2.7 Summary 78
References 79
Chapter 3 The White Point of the Light Source 85
3.1 The Location of Unique White in the Chromaticity Diagram 88
3.2 Modeling Unique White in Terms of L - M and L + M - S Signals 91
3.3 Interobserver Variability of White Tone Perception 92
3.4 White Tone Preference 97
3.5 The White Tone's Perceived Brightness 99
3.6 Summary and Outlook 101
References 103
Chapter 4 Object Colors - Spectral Reflectance, Grouping of Colored Objects, and Color Gamut Aspects 105
4.1 Introduction: Aims and Research Questions 105
4.2 Spectral Reflectance of Flowers 108
4.3 Spectral Reflectance of Skin Tones 110
4.4 Spectral Reflectance of Art Paintings 111
4.5 The Leeds Database of Object Colors 112
4.6 State-of-the-Art Sets of Test Color Samples and Their Ability to Evaluate the Color Quality of Light Sources 114
4.7 Principles of Color Grouping with Two Examples for Applications 128
4.7.1 Method 1 - Application of the Theory of Signal Processing in the Classical Approach 134
4.7.2 Method 2 - the Application of a Visual Color Model in the Classical Approach 135
4.7.3 Method 3 - the Application of Visual Color Models in the Modern Approach 135
4.7.4 First Example of Color Grouping with a Specific Lighting System Applying Two Methods 136
4.7.5 Second Example of Applying Method 3 by Using Modern Color Metrics 137
4.8 Summary and Lessons Learnt for Lighting Practice 139
References 140
Chapter 5 State of the Art of Color Quality Research and Light Source Technology: A Literature Review 143
5.1 General Aspects 143
5.2 Review of the State of the Art of Light Source Technology Regarding Color Quality 146
5.3 Review of the State of the Art of Colored Object Aspects 155
5.4 Viewing Conditions in Color Research 156
5.5 Review of the State-of-the-Art Color Spaces and Color Difference Formulae 159
5.6 General Review of the State of the Art of Color Quality Metrics 168
5.7 Review of the Visual Experiments 174
5.8 Review of the State-of-the-Art Analyses about the Correlation of Color Quality Metrics of Light Sources 175
5.9 Review of the State-of-the-Art Analysis of the Prediction Potential and Correctness of Color Quality Metrics Verified by Visual Experiments 180
References 185
Chapter 6 Correlations of Color Quality Metrics and a Two-Metrics Analysis 189
6.1 Introduction: Research Questions 189
6.2 Correlation of Color Quality Metrics 191
6.2.1 Correlation of Color Metrics for the Warm White Light Sources 192
6.2.2 Correlation of Color Quality Metrics for Cold White Light Sources 198
6.3 Color Preference and Naturalness Metrics as a Function of Two-Metrics Combinations 203
6.3.1 Color Preference with the Constrained Linear Formula (Eq. (6.2)) 206
6.3.2 Color Preference with the Unconstrained Linear Formula (Eq. (6.3)) 208
6.3.3 Color Preference with the Quadratic Saturation and Linear Fidelity Formula (Eq. (6.4)) 209
6.4 Conclusions and Lessons Learnt for Lighting Practice 210
References 212
Chapter 7 Visual Color Quality Experiments at the Technische Universität Darmstadt 215
7.1 Motivation and Aim of the Visual Color Quality Experiments 215
7.2 Experiment on Chromatic and Achromatic Visual Clarity 218
7.2.1 Experimental Method 219
7.2.2 Analysis and Modeling of the Visual Clarity Dataset 222
7.3 Brightness Matching of Strongly Metameric White Light Sources 226
7.3.1 Experimental Method 227
7.3.2 Results of the Brightness-Matching Experiment 230
7.4 Correlated Color Temperature Preference for White Objects 232
7.4.1 Experimental Method 232
7.4.2 Results and Discussion 237
7.4.3 Modeling in Terms of LMS Cone Signals and Their Combinations 237
7.4.4 Summary 239
7.5 Color Temperature Preference of Illumination with Red, Blue, and Colorful Object Combinations 239
7.5.1 Experimental Method 240
7.5.2 Results and Discussion 244
7.5.3 Modeling in Terms of LMS Cone Signals and Their Combinations 244
7.5.4 Summary 247
7.6 Experiments on Color Preference, Naturalness, and Vividness in a Real Room 248
7.6.1 Experimental Method 248
7.6.2 Relationship among the Visual Interval Scale Variables Color Naturalness, Vividness, and Preference 252
7.6.3 Correlation of the Visual Assessments with Color Quality Indices 253
7.6.4 Combinations of Color Quality Indices and Their Semantic Interpretation for the Set of Five Light Sources 254
7.6.5 Cause Analysis in Terms of Chroma Shifts and Color Gamut Differences 257
7.6.6 Lessons Learnt from Section 7.6 260
7.7 Experiments on Color Preference, Naturalness, and Vividness in a One-Chamber Viewing Booth with Makeup Products 260
7.7.1 Experimental Method 261
7.7.2 Color Preference, Naturalness, and Vividness and Their Modeling 265
7.8 Food and Makeup Products: Comparison of Color Preference, Naturalness, and Vividness Results 270
7.8.1 Method of the Experiment with Food Products 271
7.8.2 Color Preference, Naturalness, and Vividness Assessments: Merging the Results of the Two Experiments (for Multicolored Food and Reddish and Skin-Tone Type Makeup Products) 272
7.8.3 Analysis and Modeling of the Merged Results of the Two Experiments 275
7.8.4 Effect of Object Oversaturation on Color Discrimination: a Computational Approach 279
7.9 Semantic Interpretation and Criterion Values of Color Quality Metrics 282
7.9.1 Semantic Interpretation and Criterion Values of Color Differences 282
7.9.2 Semantic Interpretation and Criterion Values for the Visual Attributes of Color Appearance 290
7.10 Lessons Learnt for Lighting Practice 291
References 294
Chapter 8 Optimization of LED Light Engines for High Color Quality 297
8.1 Overview of the Development Process of LED Luminaires 297
8.2 Thermal and Electric Behavior of Typical LEDs 309
8.2.1 Temperature and Current Dependence of Warm White LED Spectra 309
8.2.2 Temperature and Current Dependence of Color LED Spectra 313
8.3 Colorimetric Behavior of LEDs under PWM and CCD Dimming 314
8.4 Spectral Models of Color LEDs and White pc-LEDs 316
8.5 General Aspects of Color Quality Optimization 319
8.6 Appropriate Wavelengths of the LEDs to Apply and a System of Color Quality Optimization for LED Luminaires 325
8.6.1 Appropriate Wavelengths of the LEDs to Apply 325
8.6.2 Systematization for the Color Quality Optimization of LED Luminaires 329
8.7 Optimization of LED Light Engines on Color Fidelity and Chroma Enhancement in the Case of Skin Tones 334
8.8 Optimization of LED Light Engines on Color Quality with the Workflow 337
8.8.1 Optimization of the LED Light Engine on Color Quality Using the RGB-W-LED Configuration 337
8.8.2 Optimization of the LED Light Engine on Color Quality with the R1 - R2 - G - B1 - B2 - W - LED - configuration 341
8.9 Conclusions: Lessons Learnt for Lighting Practice 347
References 348
Chapter 9 Human Centric Lighting and Color Quality 349
9.1 Principles of Color Quality Optimization for Human Centric Lighting 349
9.2 The Circadian Stimulus in the Rea et al. Model 352
9.3 Spectral Design for HCL: Co-optimizing Circadian Aspects and Color Quality 358
9.4 Spectral Design for HCL: Change of Spectral Transmittance of the Eye Lens with Age 362
9.5 Conclusions 368
References 369
Chapter 10 Conclusions: Lessons Learnt for Lighting Engineering 371
Index 365
EULA 385