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Advanced Techniques in Digital Halftoning: Colorimetric Modeling and Spectral Methods

This Ph.D. course offers an in-depth exploration of digital halftoning, specifically focusing on colorimetric modeling methods and their application to binary color printing. Led by Lars Bergman from Halmstad University, the course critically reviews various spectral models including Murray-Davis, Neugebauer, and Yule-Nielsen, examining mechanical and optical dot gain, effective dot area, and more. Participants will engage with practical methods and regression models to predict printer spectral outputs, enhance image quality and develop an understanding of halftoning algorithms applicable to large-format inkjet printers.

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Advanced Techniques in Digital Halftoning: Colorimetric Modeling and Spectral Methods

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  1. Ph.D. Course in Digital Halftoning Examples of Colorimetric Modeling Methods Lars Bergman, Halmstad University

  2. Papers • A Critical Review of Spectral Models Applied to Binary Color Printing • The Spectral Modeling of Large Format InkJet Printers Digital halftoning - Lars Bergman

  3. Forward • RGB -> CMY(K) Reversed • How much CMY(K) for a given RGB • Predict the spectral output of the printer • Effective dot area Digital halftoning - Lars Bergman

  4. Effective dot area • Mechanical dot gain • Ink cover larger area on paper then intended • Optical dot gain • Light spread in paper (and ink) Digital halftoning - Lars Bergman

  5. Typical machanical dot gain for a desktop inkjet printer Digital halftoning - Lars Bergman

  6. A Critical Review of Spectral Models Applied to Binary Color Printing

  7. Regression based Murray-Davis Neugebauer Yule-Nielsen Yule-Nielsen modified Neugebauer Cellular Neugebauer Yule-Nielsen with spectral depending N-value First principals models (Regressing the Neugebauer Primarys) (Expanded Murray-Davis Model) The Propability model Modeling paper spread function Models Digital halftoning - Lars Bergman

  8. Murray-Davis Digital halftoning - Lars Bergman

  9. effective area Digital halftoning - Lars Bergman

  10. Neugebauer Digital halftoning - Lars Bergman

  11. Digital halftoning - Lars Bergman

  12. Trys to correct for the non linearity in Murray-Davis model Recomended N=1.7 for offset prints Yule-Nielsen Digital halftoning - Lars Bergman

  13. Digital halftoning - Lars Bergman

  14. Combining Yule-Nielsen and Neugebauer Yule-Nielsen is used separate for each color Yule-Nielsen modified Neugebauer Digital halftoning - Lars Bergman

  15. Cellular Neugebauer Digital halftoning - Lars Bergman

  16. Yule-Nielsen with spectral depending N-value Spectral reflectance for primary cyan ramp Digital halftoning - Lars Bergman

  17. The Propability model Light path Probabilities Digital halftoning - Lars Bergman

  18. Digital halftoning - Lars Bergman

  19. Convolution with LP filter Can handle nonuniform screens/dots Computational heavy Modeling paper spread function Digital halftoning - Lars Bergman

  20. Quality meassure Spectral fitness • RMS Spectral error Tristimulus fitness • Humanly correct • ICC profiles • CIE DE Digital halftoning - Lars Bergman

  21. Model performances Digital halftoning - Lars Bergman

  22. The Spectral Modeling of Large Format InkJet Printers

  23. Screening Determing the number of colors (ink combinations) Digital halftoning - Lars Bergman

  24. HP650C HP650 use ”Scatter mode” FM-based screening Digital halftoning - Lars Bergman

  25. Testdata Primary ramp CMYRGBK Ramp Test target used to characterize each color types spectral absorptivity. Digital halftoning - Lars Bergman

  26. Meassured spectral rflectance factor data of a cyan ramp Digital halftoning - Lars Bergman

  27. Linear model prediction for 50% cyan using Murray-Davis model Digital halftoning - Lars Bergman

  28. Normalized reflectance factor spectra for cyan ramp data Digital halftoning - Lars Bergman

  29. Normalized reflectance factor spectra for cyan ramp data using Yule-Nielsen-model N=1.7 Digital halftoning - Lars Bergman

  30. Normalized reflectance factor spectra for cyan ramp data using Yule-Nielsen-model N=10 Digital halftoning - Lars Bergman

  31. Linear model prediction for 50% cyan Digital halftoning - Lars Bergman

  32. Normalized absorbtion spectra for cyan ramp data using Kubelka-Munck transparent model Digital halftoning - Lars Bergman

  33. Normalized absorptivities based on eigenvector analyses of eight possible color types. Digital halftoning - Lars Bergman

  34. Method • Evaluate halftoning algorithm in order to determine the number of possible colortypes. • Hypothesize a color formation model • Evaluate how well the hypothesized model predict primary ramps • Evaluate secondary and tertiaries ramps • Quantify the mechanical dot gain Digital halftoning - Lars Bergman

  35. Experiments • Device driver • GCR • Registration • Test target design • Printer stability Digital halftoning - Lars Bergman

  36. Optimized Yule-Nielsen n value for CMYRGBK Digital halftoning - Lars Bergman

  37. The END

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