By Henry R. Kang
Henry Kang presents the basic colour ideas and mathematical instruments to arrange the reader for a brand new period of colour replica, and for next purposes in multispectral imaging, clinical imaging, distant sensing, and computing device imaginative and prescient. This publication is meant to bridge the distance among colour technology and computational colour know-how, placing colour model, colour fidelity, colour transforms, colour show, and colour rendition within the area of vector-matrix representations and theories. Computational colour Technology bargains with colour electronic photos at the spectral point utilizing vector-matrix representations in order that the reader can learn how to strategy electronic colour pictures through linear algebra and matrix theory.
- Tristimulus Specification
- colour ideas and homes
- Chromatic edition
- CIE colour areas
- RGB colour areas
- Device-Dependent colour areas
- third-dimensional look up desk with Interpolation
- Metameric Decomposition and Reconstruction
- Spectrum Decomposition and Reconstruction
- Computational colour fidelity
- White-Point Conversion
- Multispectral Imaging
- Kubelka-Munk concept
- Light-Reflection version
- Halftone Printing types
- problems with electronic colour Imaging
- Appendix 1: Conversion Matrices
- Appendix 2: Conversion Matrices from RGB to ITU-R.BT.709/RGB
- Appendix three: Conversion Matrices from RGB to ROMM/RGB
- Appendix four: RGB Color-Encoding criteria
- Appendix five: Matrix Inversion
- Appendix 6: colour blunders of Reconstructed CRI Spectra with recognize to Measured Values
- Appendix 7: colour error of Reconstructed CRI Spectra with recognize to Measured Values utilizing Tristimulus Inputs
- Appendix eight: White-Point Conversion Accuracies utilizing Polynomial Regression
- Appendix nine: electronic Implementation of the overlaying Equation
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Additional info for Computational Color Technology (SPIE Press Monograph Vol. PM159)
31–41 (1991). 9. G. Wyszecki and W. S. Stiles, Color Science: Concept and Methods, Quantitative Data and Formulae, 2nd Edition, Wiley, New York, p. 142 (1982). 10. W. A. Thornton, Three color visual response, J. Opt. Soc. Am. 62, pp. 457–459 (1972). 11. R. G. Kuehni, Intersection nodes of metameric matches, Color Res. Appl. 4, pp. 101–102 (1979). 12. D. L. MacAdam, Photometric relationships between complementary colors, J. Opt. Soc. Am. 28, pp. 103–111 (1938). 13. G. R. Bird and R. C. Jones, Estimation of the spectral functions of the human cone pigments, J.
M (λ) = Em (λ)Sm (λ). 4) Typically, a metameric match is specific to one observer or one illuminant. When either illuminant or observer is changed, it is most common to find that the metameric match breaks down. There are some instances in which the metameric match may hold for a second illuminant. Usually, this will be true if peak reflectance values of two samples are equal at three or more wavelengths. Such samples will tend to be metameric under one light source, and if the wavelength locations of intersections are appropriate, they may continue to provide a metameric match for a second illuminant.
In all cases, the resulting color sensation given by Eq. 1) is a set of tristimulus values. org/terms Metamerism 29 color sensation. 2 Color stimulus is the cause and color sensation is the effect. Color science is built on psychophysics, where the color matching represented by the tristimulus values as coefficients is matched psychologically. 3,4 He further noted that the metameric black function is orthogonal to the space of the CMF. 5) where n is the number of samples taken in the visible spectrum.