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The LLAB model for quantifying colour appearance - Loughborough PDF

280 Pages·2016·8.69 MB·English
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Loughborough University Institutional Repository The LLAB model for quantifying colour appearance ThisitemwassubmittedtoLoughboroughUniversity’sInstitutionalRepository by the/an author. Additional Information: • A Doctoral Thesis. Submitted in partial fulfillment of the requirements for the award of Doctor of Philosophy of Loughborough University. Metadata Record: https://dspace.lboro.ac.uk/2134/9674 Publisher: (cid:13)c Mei-Chun Lo Please cite the published version. This item is held in Loughborough University’s Institutional Repository (https://dspace.lboro.ac.uk/) and was harvested from the British Library’s EThOS service (http://www.ethos.bl.uk/). It is made available under the following Creative Commons Licence conditions. For the full text of this licence, please go to: http://creativecommons.org/licenses/by-nc-nd/2.5/ THE LLAB MODEL FOR QUANTIFYING COLOUR APPEARANCE By Mei-ChunLo A Doctoral Thesis Submittedin partialfulfilment of the requirement for the awardof Doctor ofPhilosophy ofthe Loughborough University of Technology August 1995 ©Mei-ChunLo 1995 ABSTRACT A reliable colour appearance model is desired by industry to achieve high colour fidelity between images produced using a range of different imaging devices. The aim of this study was to derive a reliable colour appearance model capable of predicting the change of perceived attributes of colour appearance under a wide range of media/viewing conditions. The research was divided into three parts: characterising imaging devices, conducting a psychophysical experiment, and developing a colour appearance model. Various imaging devices were characterised including a graphic art scanner, a Cromalin proofing system, an IRIS ink jet printer, and a Barco Calibrator. For the former three devices, each colour is described by four primaries: cyan (C), magenta (M), yellow (Y), and black (K). Three set of characterisation samples (120 and 31 black printer, and cube data sets) were produced and measured for deriving and testing the printing characterisation models. Four black printer algorithms (BPA), were derived. Each included both forward and reverse processes. A 2nd BPA printing model taking into account additivity failure, grey component replacement (GCR) algorithm gave the most accurate prediction to the characterisation data set than the other BPA models. The PLCC (Piecewise Linear interpolation assuming Constant Chromaticity coordinates) monitor model was also implemented to characterise the Barco monitor. The psychophysical experiment was conducted to compare Cromalin hardcopy images viewed in a viewing cabinet and softcopy images presented on a monitor under a wide range of illuminants (white points) including: D93, D65, D50 and A. Two scaling methods: category judgement and paired comparison, were employed by viewing a pair of images. Three classes of colour models were evaluated: uniform colour spaces, colour appearance models and chromatic adaptation transforms. Six images were selected and processed via each colour model. The results indicated that the BFD chromatic transform gave the most accurate predictions of the visual results. Finally, a colour appearance model, LLAB, was developed. It is a combination of the " " BFD chromatic transform and a modified version of CIELAB uniform colour space to fit the LUTCRI Colour Appearance Data previously accumulated. The form of the LLAB model is much simpler and its performance is more precise to fit experimental data than those of the other models. ACKNOWLEDGEMENTS The author is grateful to her supervisor Dr. H. E. Bez for his work on administrative support and encouragement. The author wishes to express the most sincere thanks to her external supervisor Dr. M. R. Luo andhis guidance in the writing of this thesis. Particular thanks are due to The National Science Council, Taiwan, R.O.c., and The World College of Journalism and Communications, Taipei, Taiwan for the financial assistance. This work was also supported by Crosfield Electronics Ltd. for preparing samples and supplying the tele-spectroradiometer for colour measurement. The author would also like tothank Mr. Tony Johnson and Professor R.W. G. Hunt for their technical advice. The author is greatly indebted to every member of her family for their wonderful support andencouragement. Many thanks are also due to the people who took part many sessions of the III psychophysical experiments. CONTENTS LIST OFTABLES LIST OFFIGURES LIST OF APPENDICES Chapter 1 INTRODUCTION 1 1.1 WYSIWIG 1 1.2 Device Dependency 1 1.3 Variation of ColourAppearanceUnder Different Viewing Conditions 2 1.4 The Aim ofthe Study 2 Chapter 2 LITERATURE SURVEY 4 2.1 Colour Specification Systems 4 2.1.1 The crnSystem 4 2.1.2 ColourOrder System 6 2.1.2.1 The Munsell System 6 2.2.2.2 The Natural Color System (NCS) 7 2.2 Colour DifferenceFormulae 8 2.3 Colour MeasurementInstruments 11 2.3.1 Tele-Spectroradiometer 12 2.3.2 Spectrophotometer 12 2.4 Colour Printing 13 2.4.1 OffsetColourPrinting 13 2.4.2 Cromalin Proofing System and ContinuousInk-JetPrinting 13 2.4.3 Tone Reproduction 14 2.4.4 Black Printer and Grey ComponentReplacement (GCR) 15 Contents 2.4.4.1 Tone Reproduction for Black 15 2.4.4.2 Chromatic and Achromatic Colour Reproduction 16 2.4.4.3 GCR 17 2.4.5 Additivity Failure and Sub-AdditivityBehaviour 18 2.5 Review of Mathematical Models for Characterising Printing and Monitor Devices 19 2.5.1 Printing MathematicalModels 19 2.5.1.1 Neugebauer-Type Equations 19 2.5.1.2 Masking-TypeEquations 25 2.5.2 Monitor Models 27 2.5.2.1 PLCC (Piecewise Linearinterpolation assuming constant Chromaticity Coordinates) 28 2.5.2.2 LIN-LIN2 (Linear-Linear 2nd-OrderModel) 29 2.5.2.3 LOG-LOG (Log-Log Model) 29 2.5.2.4 LOG-LOG2 (Log-Log 2nd-OrderModel) 29 2.5.2.5 Berns et al. (ModifiedLog-Log Model) 29 2.5.2.6 LOG-LIN2 (Log-Linear2nd-OrderModel) 30 2.5.2.7 PLVC (Piecewise Linearinterpolation assuming Variable Chromaticity coordinates) 30 2.5.3 The Evaluation ofModels' Performance 30 2.5.3.1 Printing Models' Performance 30 2.5.3.2 Monitor Models' Performance 32 2.6 The Psychological Laws 34 2.6.1 The Fecher'sLogarithmic Law and the Stevens's PowerLaw 34 2.6.2 The Law of ComparativeJudgement 36 2.6.3 The Law of Categorical Judgement 38 Contents 2.7 Chromatic Adaptation and Colour Appearance 39 2.7.1 Chromatic Adaptation Theory 39 2.7.1.1 Symmetric Matching 41 2.7.1.2 AsymmetricMatching 41 2.7.2 Some ColourAppearancePhenomena 42 2.7.2.1 Discounting ofthe Illuminant Colour (Object-ColourConstancy) 42 2.7.2.2 The Helson-JuddEffect 43 2.7.2.3 TheBezold-BruckeEffect 43 2.7.2.4 The Stevens Effect 43 2.7.2.5 The Hunt Effect 44 2.7.2.6 The Helmholtz-Kohlrausch Effect 44 2.7.3 Techniques For Studying Chromatic Adaptation and Assessing ColourAppearance 44 2.7.3.1 Haploscopic Matching 45 2.7.3.1.1 Simultaneous-HaploscopicMatching 45 2.7.3.1.2 Successive-HaploscopicMatching 46 2.7.3.2 Local Adaptation 47 2.7.3.3 Direct Scaling and MagnitudeEstimation 47 2.7.3.4 Memory Matching 48 2.7.4 Chromatic AdaptationTransforms 49 2.7.4.1 The von Kries Chromatic Adaptation Transform 49 2.7.4.2 The BFD Chromatic Adaptation Transform 50 2.7.4.3 The Nayatani Chromatic Adaptation Transform (CIE Chromatic Adaptation Transform) 51 2.7.5 ColourAppearanceModels 51 Contents 2.7.5.1 The Runt Colour Appearance Model 51 2.7.5.2 The Nayatani Colour Appearance Model 53 2.7.5.3 The RLAB Colour Appearance Model 53 2.7.6 LUTCRI Colour Appearance Data 55 2.7.6.1 The Acquisition ofLUTCm ColourAppearanceData 55 2.7.6.1.1 Alvey Colour Appearance Data Set 55 2.7.6.1.2 CARISMA Colour Appearance Data Set 57 2.7.6.1.3 Kuo and Luo Colour AppearanceData Set 59 2.7.6.2 Testing ColourModels' PerformanceUsing LUTCRI ColourAppearanceData 60 Chapter 3 CHARACTERISINGPRINTING DEVICES 62 3.1 Objectives 62 3.2 Printing Devices Selected 63 3.3 Data Sets for Characterising Printers 63 3.3.1 Cube DataSet 63 3.3.2 BlackPrinterDataSet 64 3.4 Characterising Procedures 65 3.5 Printing Characterisation Models 67 3.5.1 Sub-AdditivityEquations (SAE) 69 3.5.2 Modified Sub-AdditivityEquations (MSAE) 71 3.5.3 Third-OrderPolynomial Equations (3rd) 71 3.5.4 Second-Order Polynomial Equations (2nd) 71 3.6 Testing Models' Performance 72 3.6.1 The Performance ofthe Third-OrderMasking Model 72 3.6.2 The Performance ofthe ForwardBPA Models 74 Contents 3.6.3 The Performance of the Reverse BPAModels 76 3.6.4 The Reversibility PerformanceBetween the Forward and Reverse BPA Models 78 3.7 Conclusions 81 Chapter4 QUANTIFYING COLOURAPPEARANCE-COMPLEXIMAGES 83 4.1 Experimental Preparation 84 4.1.1 Device Characterisation 84 4.1.2 Image Preparation and Processing 88 4.2 PreliminaryExperiment 89 4.2.1 Experimental Set-Up and Viewing Configuration 90 4.2.2 Data Analysis 92 4.2.3 Spatial Uniformity ofMonitor Screen 96 4.2.4 Models' Performance 96 4.3 Main Experiment 98 4.3.1 Viewing Configuration 98 4.3.2 Viewing Conditions and Viewing Techniques 99 4.4 DataAnalysis 101 4.5 Results and Discussion 102 4.5.1 ObserverPrecision and Repeatability 102 4.5.2 Models' Performance 103 4.5.3 Image Dependency 106 4.5.4 DifferenceBetween Results FromPairedComparison and Category Judgement 107 4.5.5 Image Quality ofColourFidelity 108 4.6 Conclusions 108

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EThOS service (http://www.ethos.bl.uk/). It is made available Cromalin proofing system, an IRIS ink jet printer, and a Barco Calibrator. For the former three
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