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Ph.D. Course in Digital Halftoning. Examples of Colorimetric Modeling Methods Lars Bergman, Halmstad University. Papers. A Critical Review of Spectral Models Applied to Binary Color Printing The Spectral Modeling of Large Format InkJet Printers . Forward RGB -> CMY(K) Reversed - PowerPoint PPT Presentation
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Ph.D. Course in Ph.D. Course in
Digital HalftoningDigital Halftoning
Examples of Colorimetric Modeling Examples of Colorimetric Modeling MethodsMethods
Lars Bergman, Halmstad UniversityLars Bergman, Halmstad University
23-04-2223-04-22 Digital halftoning - Lars BergmanDigital halftoning - Lars Bergman 22
PapersPapers
A Critical Review of Spectral Models A Critical Review of Spectral Models Applied to Binary Color Printing Applied to Binary Color Printing
The Spectral Modeling of Large Format The Spectral Modeling of Large Format InkJet Printers InkJet Printers
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ForwardForward RGB -> CMY(K)RGB -> CMY(K)
ReversedReversed How much CMY(K) for a given RGBHow much CMY(K) for a given RGB
– Predict the spectral output of the printerPredict the spectral output of the printer– Effective dot areaEffective dot area
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Effective dot areaEffective dot area
Mechanical dot gainMechanical dot gain– Ink cover larger area on paper then Ink cover larger area on paper then
intendedintended Optical dot gainOptical dot gain
– Light spread in paper (and ink)Light spread in paper (and ink)
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Typical machanical dot gain Typical machanical dot gain
for a desktop inkjet printerfor a desktop inkjet printer
A Critical Review of Spectral A Critical Review of Spectral Models Applied to Binary Models Applied to Binary Color PrintingColor Printing
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ModelsModels
Regression basedRegression based Murray-Davis Neugebauer Yule-Nielsen Yule-Nielsen
modified Neugebauer
Cellular Neugebauer Yule-Nielsen with
spectral depending N-value
First principals modelsFirst principals models (Regressing the
Neugebauer Primarys)
(Expanded Murray-Davis Model)
The Propability model
Modeling paper spread function
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Murray-DavisMurray-Davis
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effective areaeffective area
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NeugebauerNeugebauer
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Yule-Nielsen
Trys to correct for the non linearity in Trys to correct for the non linearity in Murray-Davis modelMurray-Davis model
Recomended N=1.7 for offset printsRecomended N=1.7 for offset prints
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Yule-Nielsen modified Neugebauer Combining Yule-Combining Yule-
Nielsen and Nielsen and NeugebauerNeugebauer
Yule-Nielsen is used Yule-Nielsen is used separate for each separate for each colorcolor
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Cellular Neugebauer
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Yule-Nielsen with spectral depending N-value
Spectral reflectance for primary
cyan ramp
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The Propability model
Light path ProbabilitiesLight path Probabilities
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Modeling paper spread function Convolution with LP filterConvolution with LP filter Can handle nonuniform Can handle nonuniform
screens/dotsscreens/dots Computational heavyComputational heavy
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Quality meassure Quality meassure
Spectral fitnessSpectral fitness RMS Spectral errorRMS Spectral error
Tristimulus fitness Tristimulus fitness – Humanly correctHumanly correct– ICC profilesICC profiles
CIE CIE EE
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Model performancesModel performances
The Spectral Modeling of The Spectral Modeling of Large Format InkJet Large Format InkJet Printers Printers
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ScreeningScreening
Determing the number of colors (ink Determing the number of colors (ink combinations)combinations)
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HP650CHP650C
HP650 use ”Scatter mode”
FM-based screening
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TestdataTestdata
Primary ramp
CMYRGBK Ramp
Test target used to
characterize each color types
spectral absorptivity.
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Meassured spectral rflectance
factor data of a cyan ramp
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Linear model prediction for
50% cyan using Murray-Davis
model
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Normalized reflectance factor
spectra for cyan ramp data
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Normalized reflectance factor
spectra for cyan ramp data
using Yule-Nielsen-model
N=1.7
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Normalized reflectance factor
spectra for cyan ramp data
using Yule-Nielsen-model
N=10
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Linear model prediction for
50% cyan
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Normalized absorbtion spectra
for cyan ramp data using
Kubelka-Munck transparent
model
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Normalized absorptivities
based on eigenvector
analyses of eight possible
color types.
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MethodMethod
1. Evaluate halftoning algorithm in order to determine the number of possible colortypes.
2. Hypothesize a color formation model3. Evaluate how well the hypothesized model
predict primary ramps4. Evaluate secondary and tertiaries ramps5. Quantify the mechanical dot gain
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ExperimentsExperiments
Device driverDevice driver GCRGCR RegistrationRegistration Test target designTest target design Printer stabilityPrinter stability
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Optimized Yule-Nielsen n value for CMYRGBK
The ENDThe END