Digital Color Imaging

by Fernandez-Maloigne, Christine; Robert-Inacio, Frederique; Macaire, Ludovic

• ISBN13: 9781848213470
• ISBN10: 1848213476
• Edition: 1st
• Format: Hardcover
• Copyright: 2012-06-18
• Publisher: Wiley-ISTE

Summary

This book addresses the fundamental aspects related to colorimetry and physiology, constancy and color appearance. It also addresses the more technical aspects related to sensors and color management screen.

Author Biography

Christine Fernandez-Maloigine is Director of the Xlim-SIC laboratory and Professor at the University of Poitiers in France. Frdrique Robert-Inacio is a researcher at IM2NP and lecturer at ISEN in Toulon, France. Ludovic Macaire is Professor at Lille 1 University in France.

Table of Contents

Foreword	p. xi
Color Representation and Processing in Polar Color Spaces	p. 1
Introduction	p. 1
Notations used in this chapter	p. 2
The HSI triplet	p. 3
Intuitive approach: basic concepts and state of the art	p. 3
Geometric approach: calculation of polar coordinates	p. 5
Processing of hue: a variable on the unit circle	p. 8
Can hue be represented as a scalar?	p. 8
Ordering based on distance from a reference hue	p. 9
Ordering with multiple references	p. 11
Determination of reference hues	p. 13
Color morphological filtering in the HSI space	p. 15
Chromatic and achromatic top-hat transforms	p. 16
Full ordering using lexicographical cascades	p. 20
Morphological color segmentation in the HSI space	p. 24
Color distances and segmentation by connective criteria	p. 25
Color gradients and watershed segmentation	p. 31
Conclusion	p. 35
Bibliography	p. 36
Adaptive Median Color Filtering	p. 41
Introduction	p. 41
Noise	p. 42
Sources of noise	p. 43
Noise modeling	p. 45
Nonlinear filtering	p. 47
Vector methods	p. 48
Median filter using bit mixing	p. 50
Median filter: methods derived from vector methods	p. 51
Vector filtering	p. 51
Switching vector and peer group filters	p. 53
Hybrid switching vector filter	p. 55
Fuzzy filters	p. 56
Adaptive filters	p. 60
Spatially adaptive filter: generic method	p. 60
Spatially adaptive median filter	p. 62
Performance comparison	p. 66
FSVF	p. 67
FRF	p. 67
PGF and FMPGF	p. 68
IPGSVF	p. 68
Vector filters and spatially adaptive median filter	p. 69
Conclusion	p. 71
Bibliography	p. 72
Anisotropic Diffusion PDEs for Regularization of Multichannel Images: Formalisms and Applications	p. 75
Introduction	p. 75
Preliminary concepts	p. 80
Local geometry in multi-channel images	p. 81
Which geometric characteristics?	p. 81
Geometry estimated using a scalar characteristic	p. 82
Di Zenzo multi-valued geometry	p. 83
PDEs for multi-channel images smoothing: overview	p. 87
Variational methods	p. 88
Divergence PDEs	p. 91
Oriented Laplacian PDEs	p. 94
Trace PDEs	p. 97
Regularization and curvature preservation	p. 102
Single smoothing direction	p. 103
Analogy with line integral convolutions	p. 105
Extension to multi-directional smoothing	p. 107
Numerical implementation	p. 109
Some applications	p. 112
Conclusion	p. 116
Bibliography	p. 116
Linear Prediction in Spaces with Separate Achromatic and Chromatic Information	p. 123
Introduction	p. 123
Complex vector 2D linear prediction	p. 124
Spectral analysis in the IHLS and L*a*b* color spaces	p. 129
Comparison of PSD estimation methods	p. 129
Study of inter-channel interference associated with color space changing transformations	p. 132
Application to segmentation of textured color images	p. 136
Prediction error distribution	p. 136
Label field estimation	p. 139
Experiments and results	p. 140
Conclusion	p. 145
Bibliography	p. 146
Region Segmentation	p. 149
Introduction	p. 149
Compact histograms	p. 150
Classical multi-dimensional histogram	p. 151
Compact multi-dimensional histogram	p. 152
Pixel classification through compact histogram analysis	p. 156
Spatio-colorimetric classification	p. 158
Introduction	p. 158
Joint analysis	p. 158
Successive analysis	p. 164
Conclusion	p. 166
Segmentation by graph analysis	p. 167
Graphs and color images	p. 167
Semi-supervised classification using graphs	p. 173
Spectral classification applied to color image segmentation	p. 176
Evaluation of segmentation methods against a "ground truth"	p. 181
Conclusion	p. 186
Bibliography	p. 187
Color Texture Attributes	p. 193
Introduction	p. 193
Concept of color texture	p. 194
Color texture feature specificities	p. 197
Image databases	p. 199
Applications involving color texture characterization	p. 201
Statistical features	p. 201
Statistical features describing color distribution	p. 202
Second-order statistical features	p. 203
Higher-order statistical features	p. 211
Conclusion	p. 213
Spatio-frequential features	p. 213
Gabour transform	p. 215
Wavelet transform	p. 216
Stochastic modeling	p. 217
Markov fields	p. 218
Linear prediction models	p. 221
Color texture classification	p. 223
Color and texture approaches	p. 224
Color texture and choice of color space	p. 226
Experimental results	p. 229
Conclusion	p. 232
Bibliography	p. 233
Photometric Color Invariants for Object Recognition	p. 241
Introduction	p. 241
Object recognition	p. 241
Compromise between discriminating power and invariance	p. 244
Content of this chapter	p. 245
Basic assumptions	p. 246
Hypotheses on color formation	p. 246
Assumptions on the reflective properties of surface elements	p. 248
Assumptions on camera sensor responses	p. 249
Assumptions on the characteristics of the illumination	p. 250
Hypotheses of the photometric and radiometric variation model	p. 252
Color invariant characteristics	p. 255
Inter- and intra-component color ratios	p. 256
Transformations based on analysis of colorimetric distributions	p. 266
Invariant derivatives	p. 268
Conclusion	p. 280
Bibliography	p. 280
Color Key Point Detectors and Local Color Descriptors	p. 285
Introduction	p. 285
Color key point and region detectors	p. 286
Detector quality criteria	p. 286
Color key points	p. 288
Color key regions	p. 293
Simulation of human visual system	p. 295
Learning for detection	p. 297
Local color descriptors	p. 299
Concatenation of two types of descriptors	p. 300
Two successive stages for image comparison	p. 302
Parallel comparisons	p. 304
Spatio-colorimetric descriptors	p. 306
Conclusion	p. 308
Bibliography	p. 309
Motion Estimation in Color Image Sequences	p. 317
Introduction	p. 317
Extension of classical motion estimation techniques to color image spaces	p. 318
Luminance images and optical flow	p. 318
Estimation of optical flow in color spaces	p. 319
Apparent motion and vector images	p. 324
Motion and structure tensor in the scalar case	p. 324
Stability of tensor spectral directions	p. 325
Vector approach to optical flow	p. 326
Conclusion	p. 334
Bibliography	p. 336
Appendix to Chapter 7: Summary of Hypotheses and Color Characteristics Invariances	p. 339
Bibliography	p. 344
List of Authors	p. 345
Index	p. 349
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