OSA's Digital Library

Journal of the Optical Society of America A

Journal of the Optical Society of America A

| OPTICS, IMAGE SCIENCE, AND VISION

  • Editor: Franco Gori
  • Vol. 31, Iss. 6 — Jun. 1, 2014
  • pp: 1284–1294

Optimization of spectral printer modeling based on a modified cellular Yule–Nielsen spectral Neugebauer model

Qiang Liu, Xiaoxia Wan, and Dehong Xie  »View Author Affiliations


JOSA A, Vol. 31, Issue 6, pp. 1284-1294 (2014)
http://dx.doi.org/10.1364/JOSAA.31.001284


View Full Text Article

Enhanced HTML    Acrobat PDF (1221 KB)





Browse Journals / Lookup Meetings

Browse by Journal and Year


   


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools

Share
Citations

Abstract

The study presented here optimizes several steps in the spectral printer modeling workflow based on a cellular Yule–Nielsen spectral Neugebauer (CYNSN) model. First, a printer subdividing method was developed that reduces the number of sub-models while maintaining the maximum device gamut. Second, the forward spectral prediction accuracy of the CYNSN model for each subspace of the printer was improved using back propagation artificial neural network (BPANN) estimated n values. Third, a sequential gamut judging method, which clearly reduced the complexity of the optimal sub-model and cell searching process during printer backward modeling, was proposed. After that, we further modified the use of the modeling color metric and comprehensively improved the spectral and perceptual accuracy of the spectral printer model. The experimental results show that the proposed optimization approaches provide obvious improvements in aspects of the modeling accuracy or efficiency for each of the corresponding steps, and an overall improvement of the optimized spectral printer modeling workflow was also demonstrated.

© 2014 Optical Society of America

OCIS Codes
(300.6550) Spectroscopy : Spectroscopy, visible
(330.1690) Vision, color, and visual optics : Color
(330.1730) Vision, color, and visual optics : Colorimetry

ToC Category:
Vision, Color, and Visual Optics

History
Original Manuscript: September 19, 2013
Revised Manuscript: March 18, 2014
Manuscript Accepted: April 21, 2014
Published: May 20, 2014

Citation
Qiang Liu, Xiaoxia Wan, and Dehong Xie, "Optimization of spectral printer modeling based on a modified cellular Yule–Nielsen spectral Neugebauer model," J. Opt. Soc. Am. A 31, 1284-1294 (2014)
http://www.opticsinfobase.org/josaa/abstract.cfm?URI=josaa-31-6-1284


Sort:  Author  |  Year  |  Journal  |  Reset  

References

  1. D. R. Wyble and R. S. Berns, “A critical review of spectral models applied to binary color printing,” Color Res. Appl. 25, 4–19 (2000). [CrossRef]
  2. J. Guo, H. Xu, and M. R. Luo, “Novel spectral characterization method for color printer based on the cellular Neugebauer model,” Chin. Opt. Lett. 8, 1106–1109 (2010). [CrossRef]
  3. S. Bianco and R. Schettini, “Sampling optimization for printer characterization by direct search,” IEEE Trans. Image Process. 21, 4868–4873 (2012). [CrossRef]
  4. D. Tzeng, “Spectral-based color separation algorithm development for multi-ink color reproduction,” Ph.D. dissertation (Rochester Institute of Technology, 1999).
  5. J. Gerhardt and J. Y. Hardeberg, “Spectral color reproduction minimizing spectral and perceptual color differences,” Color Res. Appl. 33, 494–504 (2008). [CrossRef]
  6. B. Wang, H. Xu, M. Ronnier Luo, and J. Guo, “Maintaining accuracy of cellular Yule–Nielsen spectral Neugebauer models for different ink cartridges using principal component analysis,” J. Opt. Soc. Am. A 28, 1429–1435 (2011). [CrossRef]
  7. Y. Chen, R. S. Berns, L. A. Taplin, and F. Imai, “Six color printer characterization using an optimized cellular Yule–Nielsen spectral Neugebauer model,” J. Imaging Sci. Technol. 48, 519–528 (2004).
  8. P. Urban and R. R. Grigat, “Spectral based color separation using linear regression iteration,” Color Res. Appl. 31, 229–238 (2006). [CrossRef]
  9. Y. Chen, R. Berns, L. Taplin, and F. Imai, “Multi-ink color-separation algorithm improving image quality,” J. Imaging Sci. Technol. 52, 020604 (2008). [CrossRef]
  10. C. Li and M. R. Luo, “Further accelerating the inversion of the Yule-Nielson modified Neugebauer model,” in 16th Color Imaging Conference: Color Science and Engineering Systems, Technologies, and Applications, Final Program and Proceedings—IS and T/SID Color Imaging Conference (Society for Imaging Science and Technology, 2008), pp. 84–88.
  11. L. A. Taplin, “Spectral modeling of a six-color inkjet printer,” Master thesis (Rochester Institute of Technology, 2001).
  12. M. Hebert and R. D. Hersch, “Analyzing halftone dot blurring by extended spectral prediction models,” J. Opt. Soc. Am. A 27, 6–12 (2010). [CrossRef]
  13. R. D. Hersch, P. Emmel, F. Collaud, and F. Crété, “Spectral reflection and dot surface prediction models for color halftone prints,” J. Electron. Imaging 14, 033001 (2005). [CrossRef]
  14. Q. Liu, X.-X. Wan, and H.-P. Xu, “Study on ink restriction of ink-jet printing based on spectral gamut maximization,” Spectrosc. Spect. Anal. 33, 1636–1641 (2013).
  15. P. Urban and R. Berns, “Paramer mismatch-based spectral gamut mapping,” IEEE Trans. Image Process. 20, 1599–1610 (2011). [CrossRef]
  16. P. Urban, M. R. Rosen, and R. S. Berns, “Spectral gamut mapping framework based on human color vision,” in Proceedings of the 4th European Conference on Colour in Graphics, Imaging, and Vision and 10th International Symposium on Multispectral Colour Science (Society for Imaging Science and Technology, 2008), pp. 548–553.
  17. B. Wang, H. Xu, M. R. Luo, and J. Guo, “Spectral-based color separation method for a multi-ink printer,” Chin. Opt. Lett. 9, 063301 (2011). [CrossRef]
  18. F. H. Imai, M. R. Rosen, and R. S. Berns, “Comparative study of metrics for spectral match quality,” in Proceedings of the First European Conference on Colour in Graphics, Imaging and Vision (Society for Imaging Science and Technology, 2002), pp. 492–496.
  19. B. Wang, H. Xu, and M. R. Luo, “Color separation criteria for spectral multi-ink printer characterization,” Chin. Opt. Lett. 10, 013301 (2012). [CrossRef]
  20. R. Rossier, T. Bugnon, and R. D. Hersch, “Introducing ink spreading within the cellular Yule–Nielsen modified Neugebauer model,” in Proceedings of the 18th Color and Imaging Conference: Color Science and Engineering Systems, Technologies, and Applications, Technical Papers and Proceedings (Society for Imaging Science and Technology, 2010), pp. 295–300.
  21. P. Kubelka and F. Munk, “A contribution to the optics of pigments,” Z. Tech. Phys. 12, 593–599 (1931).
  22. E. Perales, F. M. Martínez-Verdú, V. Viqueira, J. Fernández-Reche, J. A. Díaz, and J. Uroz, “Comparison of color gamuts among several types of paper with the same printing technology,” Color Res. Appl. 34, 330–336 (2009). [CrossRef]
  23. A. Lewandowski, M. Ludl, G. Byrne, and G. Dorffner, “Applying the Yule–Nielsen equation with negative n,” J. Opt. Soc. Am. A 23, 1827–1834 (2006). [CrossRef]
  24. J. D’Errico, “Inhull,” http://www.mathworks.com/matlabcentral/fileexchange/10226-inhull .
  25. E. K. Chong and S. H. Zak, An Introduction to Optimization (Wiley, 2013).

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.


« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited