Acquisition And Reproduction Of Color Images

Acquisition And Reproduction Of Color Images

by Jon Y. Hardeberg

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Product Details

ISBN-13: 9781581121353
Publisher: Universal-Publishers.com
Publication date: 08/01/2001
Pages: 328
Product dimensions: 5.50(w) x 8.50(h) x 0.73(d)

Table of Contents

Prefacei
Contentsxi
List of Figuresxvii
List of Tablesxx
1Introduction1
1.1Motivation1
1.2Dissertation outline3
1.3Notation used throughout this document5
2Color and imaging7
2.1Introduction7
2.2Light and surfaces9
2.3Color vision10
2.4Colorimetry14
2.4.1Grassmann's Laws15
2.4.2Tristimulus space16
2.4.3Color matching17
2.4.4Color matching functions20
2.4.5Metamerism20
2.4.6CIE standard illuminants21
2.4.7CIE standard observers22
2.4.8Uniform color spaces and color differences26
2.5Color imaging32
2.5.1Color management32
2.5.2Digital image acquisition37
2.5.3Digital image reproduction39
2.5.4Multi-channel imaging44
2.6Conclusion46
3Colorimetric scanner characterization47
3.1Introduction48
3.2Characterization methodology49
3.2.1Regression50
3.2.2Linearization of the scanner RGB values53
3.2.3Choice of the approximation function59
3.3Experimental results61
3.3.1Evaluation measures61
3.3.2Results62
3.3.3Generalization64
3.3.4Comparison of results with and without charactrization64
3.4Conclusion68
4High quality image capture71
4.1Introduction72
4.2High resolution digital cameras, a review74
4.2.1The VASARI project74
4.2.2Further developments under the MARC project75
4.3Experimental setup and initial calibration76
4.3.1General setup77
4.3.2CCD calibration77
4.4Correction algorithms80
4.4.1Light distribution correction80
4.4.2Inter-channel registration81
4.4.3Colorimetric correction82
4.5Post-processing83
4.5.1Mosaicing84
4.5.2Visualization and reproduction84
4.5.3Colorimetric analysis of fine art paintings85
4.6Conclusion85
5Colorimetric printer characterization89
5.1Introduction89
5.2Methodology overview92
5.3Inner structure94
5.3.1Delaunay triangulation of the CMY color gamut96
5.3.2Transport of the triangulation into CIELAB space97
5.4Surrounding structure99
5.4.1Construction of the surrounding structure in CIELAB space101
5.4.2Determination of the visibility directions102
5.4.3Determination of the fictive points in CIELAB space107
5.4.4Triangulation of the surrounding structure111
5.5CIELAB-to-CMY transformation114
5.5.1Localization of a CIELAB point in the 3D structure114
5.5.2Irregular tetrahedral interpolation115
5.5.3Color gamut mapping117
5.6Conclusion118
6Multispectral image acquisition: Theory and simulations121
6.1Introduction122
6.2Spectral characterization of the image acquisition system123
6.2.1Image acquisition system model124
6.2.2Spectral sensitivity function estimation126
6.2.3Discussion on spectral characterization140
6.3Spectral reflectance estimation from camera responses142
6.3.1Pseudo-inverse solution143
6.3.2Reconstruction exploiting a priori knowledge of the imaged objects144
6.3.3Evaluation of the spectral reflectance reconstruction145
6.4Analysis of spectral reflectance data sets145
6.4.1Principal Component Analysis147
6.4.2Effective dimension148
6.4.3Application to real reflectance data sets151
6.4.4Discussion153
6.5Choice of the analysis filters157
6.5.1Filter selection methods157
6.5.2Discussion162
6.6Evaluation of the acquisition system164
6.7Multimedia application: Illuminant simulation167
6.7.1Illuminant simulation using CIELAB space167
6.7.2Illuminant simulation using multispectral images169
6.7.3Evaluation of the two illuminant simulation methods169
6.8Conclusion172
7Multispectral image acquisition: Experimentation175
7.1Introduction176
7.2Equipment176
7.2.1CCD camera176
7.2.2Tunable filter177
7.2.3Illumination179
7.2.4Color chart180
7.3Illumination and dark current compensation182
7.4Spectral sensitivity estimation182
7.4.1Preliminary experiment183
7.4.2Estimation results185
7.5Experimental multispectral image acquisition186
7.5.1Model evaluation190
7.6Recovering colorimetric and spectrophotometric image data192
7.6.1Model-based spectral reconstruction192
7.6.2Direct colorimetric regression198
7.7Conclusion202
8Conclusions and perspectives205
Bibliography211
Citation index235
Appendices
AMathematical background243
A.1Least mean square (LMS) error minimization243
A.1.11D Interpolation Functions of degree n243
A.1.23D interpolation function of the first degree245
A.1.33D interpolation function of general degree n247
A.2Principal Component Analysis (PCA)248
A.3Singular Value Decomposition (SVD)252
A.3.1SVD of Jolliffe (1986)252
A.3.2SVD of Pratt (1978)253
A.3.3Application of the SVD to PCA254
A.3.4Application of the SVD to LMS minimization--pseudoinverse256
BColor transformation by 3D interpolation257
CScanner characterization data263
DSome printer gamuts277
EGamut mapping techniques289
FBibliography on the dimensionality of spectral reflectances293

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