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Control of Color Imaging Systems: Analysis and Design [Kõva köide]

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(Rochester Institute of Technology, New York, USA),
  • Formaat: Hardback, 696 pages, kõrgus x laius: 234x156 mm, kaal: 1111 g, 83 Tables, black and white; 48 Illustrations, color; 430 Illustrations, black and white
  • Ilmumisaeg: 27-May-2009
  • Kirjastus: CRC Press Inc
  • ISBN-10: 0849337461
  • ISBN-13: 9780849337468
Teised raamatud teemal:
Control of Color Imaging Systems: Analysis and DesignSuurem pilt
  • Formaat: Hardback, 696 pages, kõrgus x laius: 234x156 mm, kaal: 1111 g, 83 Tables, black and white; 48 Illustrations, color; 430 Illustrations, black and white
  • Ilmumisaeg: 27-May-2009
  • Kirjastus: CRC Press Inc
  • ISBN-10: 0849337461
  • ISBN-13: 9780849337468
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9780849337468.html
Märksõnad:
A Complete One-Stop Resource

While digital color is now the technology of choice for printers, the knowledge required to address the quality and productivity issues of these devices is scattered across several technologies, as is its supporting literature.

Bringing together information from diverse fields, Control of Color Imaging Systems: Analysis and Design is the first book to provide comprehensive coverage of the fundamentals and algorithms of the numerous disciplines associated with digital color printing in a single resource. The authors review the history of digital printing systems, explore its current status, and explain fundamental concepts, including: digital image formation, sampling, quantization, image coding, spot color calibration, and one- and multi-dimensional tone control of color management systems including process physics and controls.

A Complete Self-Tutorial With Over 150 Design Examples and 120 Exercise Problems

Based on the authors three decades of hands-on technical and teaching experience, the text provides engineers and technicians with an end-to-end understanding of the color printing process, and helps them build a foundation drawn from the diverse disciplines needed to manage and control digital production printers.

The control theory and methods presented in this book are state-of-the art for color printing systems; however, coverage of theoretical concepts and mathematics are kept to the basics, as the book is designed to teach hands on skills that will allow practitioners to gain an immediate understanding of quality and productivity concerns. The understanding provided will help practitioners build the technical skills needed to help pioneer the next generation of ideas, algorithms, and methods that will further expand the frontier of this rapidly evolving technology.

Arvustused

"... brings together the technical fields of imaging systems and feedback control systems in a self-contained manner. ... an excellent addition to the literature on the analysis and design of color-imaging systems. It should be recommended to anyone who wants to become familiar with state-of-the-art techniques in these areas." -- Daniel Viassolo, Vestas Technology R&D, Power Plant Department, Houston, Texas

Preface xv
Acknowledgments xix
Chapter 1 An Overview of Digital Printing Systems 1
1.1 Introduction
1
1.2 Printing and Publishing System
1
1.2.1 Business Management
2
1.2.2 Output Production
2
1.2.3 Process Management
5
1.3 Digital Front End
5
1.4 Digital Print Engine (Electrophotographic)
6
1.4.1 Image-on-Image and Tandem Print Engines
7
1.4.2 Parallel Printing Systems
8
1.5 Evolution of Controls Technology for Digital Printers—Color Controls View
10
1.6 Prepress-Based Processing
13
1.7 DFE-Based Processing
15
1.8 Print Engine-Based Processing
16
References
17
Chapter 2 Fundamentals of Digital Image Processing 19
2.1 Introduction
19
2.2 Digital Image Formation and Systems
19
2.2.1 Point Spread Function of a Defocused Lens
20
2.2.2 Point Spread Function of Motion Blur
21
2.2.3 Point Spread Function of Human Visual System
22
2.3 Optical and Modulation Transfer Functions
22
2.4 Image Sampling and Quantization
28
2.4.1 Two-Dimensional Sampling Theorem
31
2.4.2 Image Quantization
34
2.4.2.1 Uniform Quantization
34
2.4.2.2 Signal-to-Quantization Noise Ratio (SQNR)
35
2.4.2.3 Optimum Minimum Mean-Square Error Quantizer
36
2.4.2.4 Perceptual Quantization
40
2.4.2.5 Vector Quantization
41
2.5 Image Transform
46
2.5.1 Two-Dimensional Discrete Fourier Transform
46
2.5.2 Two-Dimensional Discrete Cosine Transform
57
2.5.3 Two-Dimensional Hadamard Transform
58
2.5.3.1 Inverse Hadamard Transform
59
2.6 Image Filtering
60
2.6.1 Design of 2-D FIR Filters
64
2.7 Image Resizing
68
2.7.1 Definition of Sampling Rate Conversion
68
2.7.2 Upsampling by Factor of P
69
2.7.3 Downsampling by Factor of Q
70
2.7.4 Sampling Rate Conversion by a Factor of 5
72
2.7.5 Examples of Low-Pass Filters Used for Sampling Rate Conversion
72
2.8 Image Enhancement
77
2.8.1 Unsharp Masking
77
2.8.2 Image Histogram
78
2.8.3 Histogram Equalization
80
2.9 Image Restoration
82
2.9.1 Wiener Filter Restoration
83
2.10 Image Halftoning
85
2.10.1 Error Diffusion Algorithm
88
Problems
91
References
97
Chapter 3 Mathematical Foundations 99
3.1 Introduction
99
3.2 General Continuous-Time System Description
99
3.2.1 Solution of Constant-Coefficients Linear Differential Equations
100
3.3 Laplace Transform
102
3.3.1 Inverse Laplace Transform
104
3.4 General Linear Discrete-Time Systems
107
3.4.1 Solution of Constant-Coefficients Difference Equations
108
3.5 z-Transform
110
3.5.1 Properties of z-Transform
113
3.5.2 Inverse z-Transform
120
3.5.3 Relation between the z-Transform and the Laplace Transform
125
3.6 Discrete-Time Fourier Transform
127
3.6.1 Properties of Discrete-Time Fourier Transform
127
3.6.2 Inverse DTFT
128
3.7 Two-Dimensional z-Transform
129
3.8 Two-Dimensional Discrete-Space Fourier Transform
131
3.8.1 Properties of 2-D DSFT
132
3.8.2 Inverse 2-D DSFT
132
3.9 Eigenvalues and Eigenvectors
134
3.9.1 Definition of Eigenvalue and Eigenvector
134
3.9.2 Product and Sum of Eigenvalues
137
3.9.3 Finding Characteristic Polynomial of a Matrix
138
3.9.4 Modal Matrix
139
3.9.5 Matrix Diagonalization
140
3.9.6 Definite Matrices
142
3.10 Singular Value Decomposition
144
3.10.1 Matrix Norm
146
3.10.2 Principal Components Analysis
150
3.11 Matrix Polynomials and Functions of Square Matrices
155
3.11.1 Matrix Polynomial
156
3.11.2 Infinite Series of Matrices
156
3.11.3 Cayley–Hamilton Theorem
157
3.11.4 Function of Matrices
159
3.11.4.1 Cayley–Hamilton Technique
159
3.11.4.2 Modal-Matrix Technique
161
3.11.5 Matrix Exponential Function eAt
163
3.11.6 Computing eAt Using Laplace Transform
165
3.11.7 Matrix Exponential Function Ak
166
3.12 Fundamentals of Matrix Calculus
168
3.12.1 Derivatives of a Scalar Function with Respect to a Vector
168
3.12.2 Derivatives of Quadratic Functions
170
3.12.3 Derivative of a Vector Function with Respect to a Vector
172
Problems
172
References
176
Chapter 4 State-Variable Representation 177
4.1 Introduction
177
4.2 Concept of States
177
4.3 State-Space Representation of Continuous-Time Systems
177
4.3.1 Definition of State
177
4.3.2 State Equations of Continuous-Time Systems
178
4.3.3 State-Space Equations of Electrical Systems
179
4.3.4 State-Space Equations of Mechanical Systems
182
4.4 State-Space Representation of General Continuous LTI Systems
185
4.4.1 Controllable Canonical Form
186
4.4.2 Observable Canonical Form
186
4.4.3 Transfer Function (Matrix) from State-Space Equations
187
4.5 Solution of LTI Continuous-Time State Equations
188
4.5.1 Solution of Homogeneous State Equation
188
4.5.2 Computing State-Transition Matrix
189
4.5.3 Complete Solution of State Equation
191
4.6 State-Space Representation of Discrete-Time Systems
193
4.6.1 Definition of State
193
4.6.2 State Equations
194
4.7 State-Space Representation of Discrete-Time LTI Systems
195
4.7.1 Controllable Canonical Form
195
4.7.2 Observable Canonical Form
196
4.7.3 Transfer Function (Matrix) from State-Space Equations
197
4.8 Solution of LTI Discrete-Time State Equations
198
4.8.1 Solution of Homogeneous State Equation
198
4.8.2 Computing State-Transition Matrix
199
4.8.3 Complete Solution of State Equations
201
4.9 Controllability of LTI Systems
203
4.9.1 Definition of Controllability
203
4.9.2 Controllability Condition
204
4.10 Observability of LTI Systems
205
4.10.1 Definition of Observability
206
4.10.2 Observability Condition
206
Problems
209
References
213
Chapter 5 Closed-Loop System Analysis and Design 215
5.1 Introduction
215
5.2 State Feedback
215
5.2.1 Basic Concept
215
5.2.2 Pole-Placement Design of SISO Systems
219
5.2.3 Pole-Placement Design of Multiple-Input Multiple-Output (MIMO) Systems
224
5.2.4 Relationship between Poles and the Closed-Loop System Response
227
5.3 LQR Design
227
5.3.1 Introduction
227
5.3.2 Solution of the LQR Problem
229
5.3.3 Steady-State Algebraic Riccati Equation
233
5.4 State Estimators (Observers) Design
234
5.4.1 Introduction
234
5.4.2 Full-Order Observer Design
234
5.4.3 Reduced-Order Observer Design
238
5.5 Combined State Estimation and Control
240
5.5.1 Introduction
240
5.5.2 Combined Controller and Observer
240
Problems
244
References
247
Chapter 6 Interpolation of Multidimensional Functions 249
6.1 Introduction
249
6.2 Interpolation of Uniformly Spaced Lookup Tables
250
6.2.1 Linear and Bilinear Interpolations
250
6.2.2 Trilinear Interpolation
254
6.2.3 Tetrahedral Interpolation
257
6.2.4 Sequential Linear Interpolation
262
6.3 Nonuniformly Spaced Lookup Tables
264
6.3.1 Shepard Interpolation
264
6.3.2 Moving-Matrix Interpolation
267
6.3.3 Recursive Least-Square Implementation of Moving-Matrix Algorithm
269
6.4 Lookup Table Inverse
270
6.4.1 Introduction
270
6.4.2 Inverse Printer MAP
270
6.4.3 Iteratively Clustered Interpolation
272
6.4.3.1 Selection of Step Size Parameter µ
273
6.4.3.2 Algorithm Initialization
274
6.4.4 Tetrahedral Technique
274
6.4.5 Conjugate Gradient Approach
275
6.4.6 Comparison of Different Inversion Algorithms
276
6.5 Compression of Lookup Tables
277
6.5.1 Introduction
277
6.5.2 Downsampling Using Sequential Linear Interpolation
278
6.5.3 Dynamic Optimization Algorithm
278
6.5.3.1 One-Dimensional DO Algorithm
278
6.5.3.2 Two-Dimensional DO Algorithm
280
6.5.3.3 Three-Dimensional DO Algorithm
281
6.6 Smoothing Algorithm for Multidimensional Functions
286
6.6.1 Introduction
286
6.6.2 Multidimensional Smoothing Algorithm
288
6.6.2.1 One-Dimensional Smoothing Algorithm
288
6.6.2.2 Two-Dimensional Smoothing Algorithm
289
6.6.2.3 Three-Dimensional Smoothing Algorithm
290
6.6.3 Application to Printing Systems
293
Problems
295
References
301
Chapter 7 Three-Dimensional Control of Color Management Systems 303
7.1 Introduction
303
7.2 Image Path Architecture
303
7.3 Profiling—A Complex System Problem
305
7.3.1 Tight Color Rendition Requirements
305
7.3.2 Gamut Limitation
306
7.3.3 Smoothness
306
7.3.4 ICC Workflow
307
7.3.5 Engine Conditions
307
7.4 Characterization of Color Systems
308
7.4.1 Least-Squares Estimation
308
7.4.1.1 A Linear in the Parameters Model
309
7.4.1.2 Recursive Least-Squares Estimation Algorithm
310
7.4.1.3 Piecewise Linear Models
313
7.4.2 Principal Component Analysis-Based Model
321
7.4.2.1 PCA-Based Model in Spectral Space
321
7.4.2.2 PCA-Based Modeling for Adaptive Estimation
327
7.4.2.3 Log-PCA Model (Log-PCA)
329
7.4.2.4 Piecewise Linear PCA Model
329
7.4.2.5 Yule–Nielson Corrected PCA Model
330
7.4.3 Neugebauer Model
331
7.4.3.1 Parameterized Model for Neugebauer Weights
332
7.4.3.2 Dot Area Coverages and Neugebauer Weights
335
7.4.3.3 Estimation of Dot Area Coverages Using Least Squares
337
7.4.3.4 Cellular Neugebauer Model (Lab-NB)
339
7.4.4 Device Drift Model
344
7.4.4.1 Autoregressive (AR) Model Applied to Printer Drift Prediction
344
7.4.4.2 Vector Autoregressive Model Applied to Printer Drift Prediction
347
7.5 GCR Selection and Inversion
350
7.5.1 A Simple GCR Function
351
7.5.2 Inversion of a Three-to-Three Forward Map
353
7.5.2.1 Inverse by Working on the Printer Model
354
7.5.2.2 Control-Based Inversion
355
7.5.2.3 Inverse by Iterating Directly on the Printer
359
7.5.3 Brief Review of GCR Methods
362
7.5.4 GCR Constrained 4-to-3 Inverse
364
7.5.4.1 A 4-to-3 Control-Based Inversion
365
7.5.4.2 K-Restricted GCR
366
7.5.4.3 Tricolor GCR
377
7.5.5 GCR Retrieval from Historical Profiles
379
7.5.6 K-Suppression Methods
382
7.6 Gamut-Mapping Methods
384
7.6.1 Gamut Mapping with Ray-Based Control Model
385
7.6.2 Centroid Clipping
392
7.6.3 Soft Gamut Mapping with Ray-Based Control Model
393
7.6.4 Gamut Mapping for Constant Lightness and Hue
395
7.6.5 Merit-Based Gamut Mapping
396
7.6.6 Black Point Compensation
398
7.7 Evaluation of Profiles
399
7.7.1 Gamut Utilization and Round Trip Accuracy
399
7.7.2 Gamut Corner Plots and Neutral Response
400
7.7.3 Visual Evaluation of Profiles
406
7.8 An Example Showing How to Build Multidimensional Inverse LUT
412
Problems
421
References
422
Chapter 8 One-Dimensional, Two-Dimensional, and Spot-Color Management and Control Methods 431
8.1 Introduction
431
8.2 Principles of Color Management
432
8.3 One-Dimensional Gray-Balance Calibration
433
8.4 Two-Dimensional Calibration
435
8.5 One-Dimensional and Two-Dimensional Printer Calibration Using Printer Models
436
8.5.1 One-Dimensional Channel-Wise (Independent) Calibration
436
8.5.2 Gray-Balanced Calibration
438
8.5.3 Two-Dimensional Calibration
442
8.6 One-Dimensional and Two-Dimensional Printer Calibration with State-Feedback Methods
445
8.6.1 Pole-Placement Design
449
8.6.2 Highlight and Shadow Corrections
450
8.6.2.1 Highlight Corrections
453
8.6.2.2 Shadow Corrections
454
8.6.3 Two-Dimensional Printer Calibration with State-Feedback Methods
455
8.6.4 Predictive Gray Balance
457
8.7 Spot-Color Control
459
8.7.1 Gamut Mapping for Spot-Color Control
464
8.7.2 Gamut Classes
464
8.7.3 Control Algorithm
467
8.7.4 Control Algorithm with Ink Limits
467
Problems
469
References
470
Chapter 9 Internal Process Controls 471
9.1 Introduction
471
9.2 Process Control Models—A General Control View
472
9.3 Time Hierarchical Process Control Loops
477
9.4 Level 1 Electrostatic Control System
477
9.4.1 Electrostatic Controller Design
483
9.5 State Space to Transfer Function Conversions
486
9.6 Level 2 Developability Controller
488
9.6.1 Jacobian Matrix for Developability Control
491
9.7 Steady-State Error
494
9.8 Design of the Gain Matrix
496
9.9 Level 3 Control Loops
501
9.9.1 Static TRC Inversion Process
505
9.9.2 Control-Based TRC Inversion Process
509
9.10 Dead Beat Response
513
9.11 TC Control Loop
515
9.11.1 Open-Loop TC Model
515
9.11.2 Design of a TC Control Loop Using a PI Controller
517
9.11.3 Design of a TC Control Loop with a Time Delay Using a PI Controller
522
9.11.4 Feedforward Compensation for Image Disturbance
525
9.11.5 Design of TC Control Loop with State Feedback Controller and State Estimator
526
9.12 Process Controls Under Limited Actuation
530
9.13 Optimal Controls for Selective States
539
9.14 Optimal Measurements
543
Problems
549
References
552
Chapter 10 Printing System Models 557
10.1 Introduction
557
10.2 Process Models
557
10.2.1 Charging Model
558
10.2.2 Exposure Model
562
10.2.3 Development Model
569
10.2.4 Transfer Model
577
10.2.5 Fusing Model
584
10.2.6 Color Model
586
10.2.6.1 Sensitivity Analysis of the Model
593
10.3 Modulation Transfer Functions
597
10.4 Tone Reproduction Curve
605
10.5 Image Simulation with Fusing and Color Models
606
10.6 Virtual Printer Color Gamut
608
10.7 Virtual Printer Model Tuning to an Experimental Printer
610
10.7.1 Tuning Toner Master Curves
610
10.7.2 Tuning of Single Separation Coefficients
612
10.7.3 Determination of Color Mixing Coefficients {Cji}
613
10.7.4 One-Dimensional Channel-Wise TRC Matching
615
10.7.5 Tuning Results
617
10.7.6 Summary
618
Problems
618
References
619
Appendix A 623
Appendix B 641
Appendix C 645
Index 647
Mestha, Lalit K.; Dianat, Sohail A.