Computational Colour Technology illustrated ed Edition

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Henry Kang provides the fundamental color principles and mathematical tools to prepare the reader for a new era of color reproduction, and for subsequent applications in multispectral imaging, medical imaging, remote sensing, and machine vision. This book is intended to bridge the gap between color science and computational color technology, putting color adaptation, color constancy, color transforms, color display, and color rendition in the domain of vector-matrix representations and theories. Computational Color Technology deals with color digital images onthe spectral level using vector-matrix representations so that the reader can learn to process digital color images via linear algebra and matrix theory. Contents - Preface - Acknowledgments - Tristimulus Specification - Color Principles and Properties - Metamerism - Chromatic Adaptation - CIE Color Spaces - RGB Color Spaces - Device-Dependent Color Spaces - Regression - Three-Dimensional Lookup Table with Interpolation - Metameric Decomposition and Reconstruction - Spectrum Decomposition and Reconstruction - Computational Color Constancy - White-Point Conversion - Multispectral Imaging - Densitometry - Kubelka-Munk Theory - Light-Reflection Model - Halftone Printing Models - Issues of Digital Color Imaging - Appendix 1: Conversion Matrices - Appendix 2: Conversion Matrices from RGB to ITU-R.BT.709/RGB - Appendix 3: Conversion Matrices from RGB to ROMM/RGB - Appendix 4: RGB Color-Encoding Standards - Appendix 5: Matrix Inversion - Appendix 6: Color Errors of Reconstructed CRI Spectra with Respect to Measured Values - Appendix 7: Color Errors of Reconstructed CRI Spectra with Respect to Measured Values Using Tristimulus Inputs - Appendix 8: White-Point Conversion Accuracies Using Polynomial Regression - Appendix 9: Digital Implementation of the Masking Equation - Index