CIELUV

Abstract: Since the adoption of the color spaces CIELAB and CIELUV by the CIE in 1976, several other uniform spaces have been developed. We studied most of these spaces and evaluated their uniformity for small as well as larger color differences. Therefore, several criteria have been defined based on color discrimination data and appearance systems. The main difference between color spaces based on discrimination data and spaces that model appearance systems is reflected in a different size of the chroma distance unit compared with the lightness unit. If spaces based on the same kind of data (discrimination data or appearance systems) are compared with each other, they are all almost equally uniform. BFD (l:c), for example, is said to be more uniform than CMC(l:c), but, based on confidence intervals of 65%, there is no significant difference between them. If the proposed color difference formula of the CIE is compared with these distance functions, it also performs equally well. The SVF space and OSA 90 space on the other hand should be better than OSA 74. However, as opposed to what was expected, OSA 74 is slightly better; but, also in this case, the difference between the spaces is insignificant.

Abstract: About the Authors. Series Preface. Preface. Introduction. 1 Light, Vision and Photometry. 1.1 Light. 1.2 Mechanism of the Human Eye. 1.3 Adaptation and Responsivity of the Human Eye. 1.4 Spectral Responsivity and the Standard Photometric Observer. 1.5 Definition of Photometric Quantities. 1.6 Photometric Units. 1.7 Calculation and Measurement of Photometric Quantities. 1.8 Relations Between Photometric Quantities. Note 1.1 Luminous Exitance, Illuminance, and Luminance of a Perfect Diffusing Plane Light Source. Note 1.2 Luminance and Brightness. 2 Color Vision and Color Specification Systems. 2.1 Mechanism of Color Vision. 2.2 Chemistry of Color Vision. 2.3 Color Specification and Terminology. 2.4 Munsell Color System. 2.5 Color System Using Additive Color Mixing. Note 2.1 Colorfulness, Chroma and Saturation. 3 CIE Standard Colorimetric System. 3.1 RGB Color Specification System. 3.2 Conversion into XYZ Color Specification System. 3.3 X10Y10Z10 Color Specification System. 3.4 Tristimulus Values and Chromaticity Coordinates. 3.5 Metamerism. 3.6 Dominant Wavelength and Purity. 3.7 Color Temperature and Correlated Color Temperature. 3.8 Illuminants and Light Sources. 3.9 Standard and Supplementary Illuminants. Note 3.1 Derivation of Color Matching Functions from Guild and Wright's Results. Note 3.2 Conversion between Color Specification Systems. Note 3.3 Conversion into XYZ Color Specification System. Note 3.4 Imaginary Colors [X] and [Z]. Note 3.5 Photometric Quantities in the X10Y10Z10 Color System. Note 3.6 Origin of the Term 'Metamerism'. Note 3.7 Simple Methods for Obtaining Correlated Color Temperature. Note 3.8 Color Temperature Conversion Filter. Note 3.9 Spectral Distribution of Black-body Radiation. 4 Uniform Color Spaces. 4.1 Uniform Chromaticity Diagrams. 4.2 Uniform Lightness Scales (ULS). 4.3 CIE Uniform Color Spaces. 4.4 Correlates of Perceived Attributes. 4.5 Comparing CIELAB and CIELUV Color Spaces. 4.6 Conversion of Color Difference. 4.7 Color Difference Equations Based on CIELAB. Note 4.1 Calculation of Munsell Value V from Luminous Reflectance Y. Note 4.2 Modified CIELAB and CIELUV Equations for Dark Colors. Note 4.3 Other Color Difference Formulas. Note 4.4 Direct Calculation of Hue Difference &delta H. 5 Measurement and Calculation of Colorimetric Values. 5.1 Direct Measurement of Tristimulus Values. 5.2 Spectral Colorimetry. 5.3 Geometrical Conditions for Measurement. 5.4 Calculation of Colorimetric Values. 5.5 Colorimetric Values in CIELAB and CIELUV Uniform Color Spaces. Note 5.1 Spectral Colorimetry of Fluorescent Materials. Note 5.2 Reference Standard for Reflection Measurements. 6 Evolution of CIE Standard Colorimetric System. 6.1 Additive Mixing. 6.2 Subtractive Mixing. 6.3 Maximum Value of Luminous Efficacy and Optimal Colors. 6.4 Chromatic Adaptation Process. 6.5 von Kries' Predictive Equation for Chromatic Adaptation. 6.6 CIE Predictive Equations for Chromatic Adaptation. 6.7 Color Vision Models. 6.8 Color Appearance Models. 6.9 Analysis of Metamerism. Note 6.1 Color Mixing Rule. Note 6.2 Lambert-Beer Law. Note 6.3 Method for Calculating the Maximum Value of the Luminous Efficacy of Radiation. Note 6.4 Method for Calculating Optimal Colors. Note 6.5 Method for Obtaining Fundamental Spectral Responsivities. Note 6.6 Deducing von Kries' Predictive Equation for Chromatic Adaptation. Note 6.7 Application of von Kries' Equation for Chromatic Adaptation. Note 6.8 Application of CIE 1994 Chromatic Adaptation Transform. Note 6.9 Theoretical Limits for Deviation from Metamerism. 7 Application of CIE Standard Colorimetric System. 7.1 Evaluation of the Color Rendering Properties of Light Sources. 7.2 Evaluation of the Spectral Distribution of Daylight Simulators. 7.3 Evaluation of Whiteness. 7.4 Evaluation of Degree of Metamerism for Change of Illuminant. 7.5 Evaluation of Degree of Metamerism for Change of Observer. 7.6 Designing Spectral Distributions of Illuminants. 7.7 Computer Color Matching. Note 7.1 Computation Method for Prescribed Spectral Distributions. Appendix I Basic Units and Terms. AI.1 SI Units. AI.2 Prefixes for SI Units. AI.3 Fundamental Constants. AI.4 Greek Letters. Appendix II Matrix Algebra. AII.1 Addition and Subtraction of Matrices. AII.2 Multiplication of Matrices. AII.3 Inverse Matrix. AII.4 Transpose Matrix. Appendix III Partial Derivatives. Appendix IV Tables. References. Bibliography. Index.

Abstract: Important standards for device-independent color allow many different color encodings. This freedom obliges users of these standards to choose the color space in which to represent their data. A device-independent interchange color space must exhibit an exact mapping to a colorimetric color representation, ability to encode all visible colors, compact representation for given accuracy, and low computational cost for transforms to and from device-dependent spaces. The performance of CIE 1931 XYZ, CIELUV, CIELAB, YES, CCIR 601-2 YCbCr, and SMPTE-C RGB is measured against these requirements. With extensions, all of these spaces can meet the first two requirements. Quantizing error dominates the representational errors of the tested color spaces. Spaces that offer low quantization error also have low gain for image noise. All linear spaces are less compact than nonlinear alternatives. The choice of nonlinearity is not critical; a wide range of gammas yields acceptable results. The choice of primaries for RGB representations is not critical, except that high-chroma primaries should be avoided. Quantizing the components of the candidate spaces with varying precision yields only small improvements. Compatibility with common image data compression techniques leads to the requirement for low luminance contamination, a property that compromises several otherwise acceptable spaces. The conversion of a device-independent representation to popular device spaces by means of trilinear interpolation requires substantially fewer lookup table entries with CCIR 601-2 YCbCr and CIELAB.