Cover -- Title Page -- Copyright -- Contents -- Preface -- Chapter 1 Introduction -- References -- Chapter 2 Color Appearance and Color Quality: Phenomena and Metrics -- 2.1 Color Vision -- 2.2 Colorimetry -- 2.2.1 Color-Matching Functions and Tristimulus Values -- 2.2.2 Chromaticity Diagram -- 2.2.3 Interobserver Variability of Color Vision -- 2.2.4 Important Concepts Related to the Chromaticity Diagram -- 2.2.5 MacAdam Ellipses and the u′ − v′ Chromaticity Diagram -- 2.3 Color Appearance, Color Cognition -- 2.3.1 Perceived Color Attributes -- 2.3.2 Viewing Conditions, Chromatic Adaptation, and Other Phenomena -- 2.3.3 Perceived Color Differences -- 2.3.4 Cognitive Color, Memory Color, and Semantic Interpretations -- 2.4 The Subjective Impression of Color Quality and Its Different Aspects -- 2.5 Modeling of Color Appearance and Perceived Color Differences -- 2.5.1 CIELAB Color Space -- 2.5.2 The CIECAM02 Color Appearance Model -- 2.5.3 Brightness Models -- 2.5.4 Modeling of Color Difference Perception in Color Spaces -- 2.6 Modeling of Color Quality -- 2.6.1 Color Fidelity Indices -- 2.6.2 Color Preference Indices -- 2.6.3 Color Gamut Indices -- 2.6.4 Color Discrimination Indices -- 2.7 Summary -- References -- Chapter 3 The White Point of the Light Source -- 3.1 The Location of Unique White in the Chromaticity Diagram -- 3.2 Modeling Unique White in Terms of L -- M and L + M -- S Signals -- 3.3 Interobserver Variability of White Tone Perception -- 3.4 White Tone Preference -- 3.5 The White Tone's Perceived Brightness -- 3.6 Summary and Outlook -- References -- Chapter 4 Object Colors -- Spectral Reflectance, Grouping of Colored Objects, and Color Gamut Aspects -- 4.1 Introduction: Aims and Research Questions -- 4.2 Spectral Reflectance of Flowers -- 4.3 Spectral Reflectance of Skin Tones -- 4.4 Spectral Reflectance of Art Paintings.

4.5 The Leeds Database of Object Colors -- 4.6 State-of-the-Art Sets of Test Color Samples and Their Ability to Evaluate the Color Quality of Light Sources -- 4.7 Principles of Color Grouping with Two Examples for Applications -- 4.7.1 Method 1 -- Application of the Theory of Signal Processing in the Classical Approach -- 4.7.2 Method 2 -- the Application of a Visual Color Model in the Classical Approach -- 4.7.3 Method 3 -- the Application of Visual Color Models in the Modern Approach -- 4.7.4 First Example of Color Grouping with a Specific Lighting System Applying Two Methods -- 4.7.5 Second Example of Applying Method 3 by Using Modern Color Metrics -- 4.8 Summary and Lessons Learnt for Lighting Practice -- References -- Chapter 5 State of the Art of Color Quality Research and Light Source Technology: A Literature Review -- 5.1 General Aspects -- 5.2 Review of the State of the Art of Light Source Technology Regarding Color Quality -- 5.3 Review of the State of the Art of Colored Object Aspects -- 5.4 Viewing Conditions in Color Research -- 5.5 Review of the State-of-the-Art Color Spaces and Color Difference Formulae -- 5.6 General Review of the State of the Art of Color Quality Metrics -- 5.7 Review of the Visual Experiments -- 5.8 Review of the State-of-the-Art Analyses about the Correlation of Color Quality Metrics of Light Sources -- 5.9 Review of the State-of-the-Art Analysis of the Prediction Potential and Correctness of Color Quality Metrics Verified by Visual Experiments -- References -- Chapter 6 Correlations of Color Quality Metrics and a Two-Metrics Analysis -- 6.1 Introduction: Research Questions -- 6.2 Correlation of Color Quality Metrics -- 6.2.1 Correlation of Color Metrics for the Warm White Light Sources -- 6.2.2 Correlation of Color Quality Metrics for Cold White Light Sources.

6.3 Color Preference and Naturalness Metrics as a Function of Two-Metrics Combinations -- 6.3.1 Color Preference with the Constrained Linear Formula (Eq. (6.2)) -- 6.3.2 Color Preference with the Unconstrained Linear Formula (Eq. (6.3)) -- 6.3.3 Color Preference with the Quadratic Saturation and Linear Fidelity Formula (Eq. (6.4)) -- 6.4 Conclusions and Lessons Learnt for Lighting Practice -- References -- Chapter 7 Visual Color Quality Experiments at the Technische Universität Darmstadt -- 7.1 Motivation and Aim of the Visual Color Quality Experiments -- 7.2 Experiment on Chromatic and Achromatic Visual Clarity -- 7.2.1 Experimental Method -- 7.2.2 Analysis and Modeling of the Visual Clarity Dataset -- 7.3 Brightness Matching of Strongly Metameric White Light Sources -- 7.3.1 Experimental Method -- 7.3.2 Results of the Brightness-Matching Experiment -- 7.4 Correlated Color Temperature Preference for White Objects -- 7.4.1 Experimental Method -- 7.4.2 Results and Discussion -- 7.4.3 Modeling in Terms of LMS Cone Signals and Their Combinations -- 7.4.4 Summary -- 7.5 Color Temperature Preference of Illumination with Red, Blue, and Colorful Object Combinations -- 7.5.1 Experimental Method -- 7.5.2 Results and Discussion -- 7.5.3 Modeling in Terms of LMS Cone Signals and Their Combinations -- 7.5.4 Summary -- 7.6 Experiments on Color Preference, Naturalness, and Vividness in a Real Room -- 7.6.1 Experimental Method -- 7.6.2 Relationship among the Visual Interval Scale Variables Color Naturalness, Vividness, and Preference -- 7.6.3 Correlation of the Visual Assessments with Color Quality Indices -- 7.6.4 Combinations of Color Quality Indices and Their Semantic Interpretation for the Set of Five Light Sources -- 7.6.5 Cause Analysis in Terms of Chroma Shifts and Color Gamut Differences -- 7.6.6 Lessons Learnt from Section 7.6.

7.7 Experiments on Color Preference, Naturalness, and Vividness in a One-Chamber Viewing Booth with Makeup Products -- 7.7.1 Experimental Method -- 7.7.2 Color Preference, Naturalness, and Vividness and Their Modeling -- 7.8 Food and Makeup Products: Comparison of Color Preference, Naturalness, and Vividness Results -- 7.8.1 Method of the Experiment with Food Products -- 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) -- 7.8.3 Analysis and Modeling of the Merged Results of the Two Experiments -- 7.8.4 Effect of Object Oversaturation on Color Discrimination: a Computational Approach -- 7.9 Semantic Interpretation and Criterion Values of Color Quality Metrics -- 7.9.1 Semantic Interpretation and Criterion Values of Color Differences -- 7.9.2 Semantic Interpretation and Criterion Values for the Visual Attributes of Color Appearance -- 7.10 Lessons Learnt for Lighting Practice -- References -- Chapter 8 Optimization of LED Light Engines for High Color Quality -- 8.1 Overview of the Development Process of LED Luminaires -- 8.2 Thermal and Electric Behavior of Typical LEDs -- 8.2.1 Temperature and Current Dependence of Warm White LED Spectra -- 8.2.2 Temperature and Current Dependence of Color LED Spectra -- 8.3 Colorimetric Behavior of LEDs under PWM and CCD Dimming -- 8.4 Spectral Models of Color LEDs and White pc-LEDs -- 8.5 General Aspects of Color Quality Optimization -- 8.6 Appropriate Wavelengths of the LEDs to Apply and a System of Color Quality Optimization for LED Luminaires -- 8.6.1 Appropriate Wavelengths of the LEDs to Apply -- 8.6.2 Systematization for the Color Quality Optimization of LED Luminaires -- 8.7 Optimization of LED Light Engines on Color Fidelity and Chroma Enhancement in the Case of Skin Tones.

8.8 Optimization of LED Light Engines on Color Quality with the Workflow -- 8.8.1 Optimization of the LED Light Engine on Color Quality Using the RGB-W-LED Configuration -- 8.8.2 Optimization of the LED Light Engine on Color Quality with the R1 -- R2 -- G -- B1 -- B2 -- W -- LED -- configuration -- 8.9 Conclusions: Lessons Learnt for Lighting Practice -- References -- Chapter 9 Human Centric Lighting and Color Quality -- 9.1 Principles of Color Quality Optimization for Human Centric Lighting -- 9.2 The Circadian Stimulus in the Rea et al. Model -- 9.3 Spectral Design for HCL: Co-optimizing Circadian Aspects and Color Quality -- 9.4 Spectral Design for HCL: Change of Spectral Transmittance of the Eye Lens with Age -- 9.5 Conclusions -- References -- Chapter 10 Conclusions: Lessons Learnt for Lighting Engineering -- Index -- EULA.