Light Scattering in Paper and Its Effect on Halftone Reproduction

Emmel

Collaud

et al. 2005

J. Electron. Imaging

Section: ͑4͒mentioning

confidence: 99%

Spectral reflection and dot surface prediction models for color halftone prints

Emmel

Collaud

et al. 2005

J. Electron. Imaging

“…Both Gaussian line spread functions [20], [21] and exponential point spread functions were proposed [22], [23], [24]. Since the point spread function can also be viewed as a probability density, probability models were proposed to describe the lateral scattering of light within the paper bulk [25], [26], [27], [28].…”

Section: The Yule-nielsen Modified Spectral Neugebauer Model and Relamentioning

confidence: 99%

Improving the Yule-Nielsen modified Neugebauer model by dot surface coverages depending on the ink superposition conditions

Crété

2005

SPIE Proceedings

Dot gain is different when dots are printed alone, printed in superposition with one ink or printed in superposition with two inks. In addition, the dot gain may also differ depending on which solid ink the considered halftone layer is superposed. In a previous research project, we developed a model for computing the effective surface coverage of a dot according to its superposition conditions. In the present contribution, we improve the Yule-Nielsen modified Neugebauer model by integrating into it our effective dot surface coverage computation model. Calibration of the reproduction curves mapping nominal to effective surface coverages in every superposition condition is carried out by fitting effective dot surfaces which minimize the sum of square differences between the measured reflection density spectra and reflection density spectra predicted according to the Yule-Nielsen modified Neugebauer model. In order to predict the reflection spectrum of a patch, its known nominal surface coverage values are converted into effective coverage values by weighting the contributions from different reproduction curves according to the weights of the contributing superposition conditions. We analyze the colorimetric prediction improvement brought by our extended dot surface coverage model for clustered-dot offset prints, thermal transfer prints and ink-jet prints. The color differences induced by the differences between measured reflection spectra and reflection spectra predicted according to the new dot surface estimation model are quantified on 729 different cyan, magenta, yellow patches covering the full color gamut. As a reference, these differences are also computed for the classical Yule-Nielsen modified spectral Neugebauer model incorporating a single halftone reproduction curve for each ink. Taking into account dot surface coverages according to different superposition conditions considerably improves the predictions of the Yule-Nielsen modified Neugebauer model. In the case of offset prints, the mean difference between predictions and measurements expressed in CIE-LAB CIE-94 ∆E 94 values is reduced at 100 lpi from 1.54 to 0.90 (accuracy improvement factor: 1.7) and at 150 lpi it is reduced from 1.87 to 1.00 (accuracy improvement factor: 1.8). Similar improvements have been observed for a thermal transfer printer at 600 dpi, at lineatures of 50 and 75 lpi. In the case of an ink-jet printer at 600 dpi, the mean ∆E 94 value is reduced at 75 lpi from 3.03 to 0.90 (accuracy improvement factor: 3.4) and at 100 lpi from 3.08 to 0.91 (accuracy improvement factor: 3.4). Downloaded From: http://proceedings.spiedigitallibrary.org/ on 06/25/2016 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx SPIE-IS&T/Vol. 5667 435 Downloaded From: http://proceedings.spiedigitallibrary.org/ on 06/25/2016 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx SPIE-IS&T/Vol. 5667 443 Downloaded From: http://proceedings.spiedigitallibrary.org/ on 06/25/2016 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx

“…Much research was carried out in building models by assuming various mathematical formulations of the point spread function H(x, y). Both Gaussian line spread functions [9], [10] and exponential point spread functions were proposed [11], [12], [13]. Since the point spread function can also be viewed as a probability density, probability models were proposed to describe the lateral scattering of light within the paper bulk [14], [15], [16].…”

Section: Existing Approaches To Spectral Color Predictionmentioning

confidence: 99%

“…; effective surface coverage of cyan only (11) m The performance of this simple ink spreading model is illustrated by the prediction accuracies in the second row ("dot gain and ink spreading according to the print order") of the tables shown in the Appendix, both for the Clapper-Yule model and for our new spectral prediction model. The increase in prediction accuracy, compared with standard single ink dot gain optimization is important: for offset prints, the mean difference between predicted and measured spectra, expressed in CIE-LAB is reduced by 25% to 50%.…”

Section: Fig 4 Spectral Prediction Model With Dot Gain and Ink Spreamentioning

confidence: 99%

Spectral prediction and dot surface estimation models for halftone prints

Color Imaging IX: Processing, Hardcopy, and Applications

Collaud

Crété

et al. 2003

We propose a new spectral prediction model as well as new approaches for modeling ink spreading which occurs when printing ink layer superpositions. The spectral prediction model enhances the classical Clapper-Yule model by taking into account the fact that proportionally more incident light through a given colorant surface is reflected back onto the same colorant surface than onto other colorant surfaces. This is expressed by a weighted mean between a component specifying the part of the incident light which exits through the same colorant as the colorant from which it enters (Saunderson corrected Neugebauer component) and a component specifying the part of the incident light whose emerging light components exit from all colorants, with a probability to exit from a given colorant equal to that colorant surface coverage (Clapper-Yule component). We also propose two models for taking into account ink spreading, a phenomenon which occurs when printing an ink halftone in superposition with one or several solid inks. Besides the physical dot gain present within a single ink halftone print, we consider in the first model the ink spreading which occurs when an ink halftone is printed on top of one or two solid inks. In the second more advanced model, we generalize this concept to ink halftones printed on top or below solid inks. We formulate for both ink spreading models systems of equations which allow to compute effective ink coverages as a combination of the individual ink coverages which occur in the different superposition cases. The new spectral prediction model combined with advanced ink spreading yields excellent spectral predictions for clustered-dot color halftone prints, both in the case of offset (75 to 150 lpi) and in the case of thermal transfer printers (50 to 75 lpi).