Color Prediction and Separation Models in Printing: Minimizing the Colorimetric and Spectral Differences employing Multiple Characterization Curves
2013 (English)Doctoral thesis, monograph (Other academic)
Color prediction models and color separation models are essential for print device characterization and calibration, from which the profiles used in color management systems are built up. Dot gain refers to the phenomenon in printing causing the printed ink dots appear bigger than their reference size in the original bitmap.The characterization of dot gain is necessary and crucial in color prediction models.
Most prediction and separation models use a single dot gain characterization curve for each primary ink. In this thesis, the dot gain behavior of each ink is characterized by using multiple characterization curves based on CIEXYZ tri-stimulus values or spectral reflectance at different subintervals. For higher color prediction accuracy, an effective coverage map is created based on those multiple characterization curves. With this map, given any reference ink combination, the effective coverage values of the involved inks are calculated by cubic interpolation, and then used to predict the tri-stimulus values or the spectra of the printed colors. The color prediction accuracy is improved significantly by using this effective coverage map. Further improvement on the modified model is also carried out by selecting optimal training samples.
Based on this color prediction model (forward model), a simple color separation model (inverse model), minimizing the colorimetric and spectral differences, is also presented. The presented color separation model shows favorable stability and gives accurate color reproduction. Ink saving is feasible during the color separation by setting tolerances in colorimetric differences (ΔE94). The simplicity and high accuracy of the proposed color prediction and separation models prove their potential to be applied to color management in practical printing systems.
In order to investigate the possibility of applying these models to multi-channel printing, color prediction for CMYLcLm prints, i.e. with the additional colorants light cyan and light magenta, is carried out using the forward model. The color prediction is implemented by treating the combination of C and Lc (M and Lm) as a new ink coordinate to replace the ink coordinate C (M) in our three-channel color prediction model. The corresponding prediction results are acceptable. Suggestions are also given for future work to simplify and modify the approach based on our simple color prediction model for CMYLmLc prints.
Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2013. , 163 p.
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1540
Engineering and Technology
IdentifiersURN: urn:nbn:se:liu:diva-97569ISBN: 978-91-7519-524-7OAI: oai:DiVA.org:liu-97569DiVA: diva2:648896
2013-10-11, TP2, Täppan, Campus Norrköping, Linköpings universitet, Norrköping, 10:00 (English)
Hersch, Roger D., Professor
Gooran, Sasan, Dr.