The CIECAM02 color-appearance model enjoys popularity in scientific research and industrial applications since it was recommended by the CIE in 2002. However, it has been found that computational failures can occur in certain cases such as during the image processing of cross-media color reproduction applications. Some proposals have been developed to repair the CIECAM02 model. However, all the proposals developed have the same structure as the original CIECAM02 model and solve the problems concerned at the expense of losing accuracy of predicted visual data compared with the original model. In this article, the structure of the CIECAM02 model is changed and the color and luminance adaptations to the illuminant are completed in the same space rather than in two different spaces, as in the original CIECAM02 model. It has been found that the new model (named CAM16) not only overcomes the previous problems, but also the performance in predicting the visual results is as good as if not better than that of the original CIECAM02 model. Furthermore the new CAM16 model is simpler than the original CIECAM02 model. In addition, if considering only chromatic adaptation, a new transformation, CAT16, is proposed to replace the previous CAT02 transformation. Finally, the new CAM16-UCS uniform color space is proposed to replace the previous CAM02-UCS space. A new complete solution for color-appearance prediction and color-difference evaluation can now be offered.

Comprehensive color solutions: CAM16, CAT16, and CAM16-UCS

Reliable color reproduction can be achieved by establishing, using a model, the correspondence between the spectral reflectance of the printed surface and the amounts of deposited inks. In this paper, we review the main models proposed in the literature, recall how each one is calibrated and compare their prediction accuracy for several print sets. The presented models are the Yule-Nielsen modified spectral Neugebauer model, its cellular instance, the Clapper-Yule model, its instance supporting low scattering, and the two-by-two halftone independent dot centering model. The Yule-Nielsen and Clapper-Yule based models are combined with ink spreading assessment methods that account for the interaction between light, inks and paper. The prediction accuracy of the different models has been tested for several sets of printed colors on different supports, with different printing systems, different inks and different halftoning methods. These results show how the predictive performances and the model parameters vary according to the different printing setups.

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Review of spectral reflectance models for halftone prints: Principles, Calibration, and prediction accuracy

We propose an extension of the cellular Yule-Nielsen spectral Neugebauer model accounting for ink spreading of each ink within each subdomain. Characterization of the ink spreading within a given subdomain is performed by fitting the mid-range weights of subdomain node reflectances with the goal of minimizing the sum of square differences between predicted and measured mid-range reflectances. We show that the mid-range weights within a subdomain can be either separately fitted on three halftones or jointly fitted on a single halftone. Accounting for ink spreading considerably improves the prediction accuracy and requires only one additional measurement per subdomain. These additional measurements do not necessarily require spectral measurements. Instead, ink spreading can also be characterized with red, green and blue sensor responses without decreasing the model reflectance prediction accuracy.

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Introducing ink spreading within the cellular Yule-Nielsen modified Neugebauer model

The present invention enables creating authenticable multi-ink luminescent continuous tone color halftone images offering means of verifying their authenticity. The invented luminescent color halftone image synthesizing techniques enable increasing the attractiveness and aesthetics of color images. The invention relies on daylight luminescent inks, color prediction models for daylight luminescent halftones, color gamuts of luminescent and non-luminescent inks, color separation into luminescent and non-luminescent ink layers, mapping of input gamuts into a luminescent target gamuts by gamut reduction and/or expansion strategies, and luminescent color halftone image generation. The basic authentication is performed by examining the excitation trace image of the synthesized luminescent color halftone image under an illuminant active within its excitation wavelength range. Further authentication means include hiding messages under one or several different illuminants as well as hiding message with different sets of luminescent inks. Hidden messages are recovered under illuminants different from their reference illuminant.

Synthesis of authenticable luminescent color halftone images

The present invention enables creating authenticable continuous tone color multi-ink multi-halftone images offering means of verifying their authenticity. The invention relies on color halftones, color separation into different ink surface coverages for different halftoning methods, mapping of an input gamut into a gamut defined by a set of inks, calculating the optimal boundary between region halftones created with different halftoning methods, and color multi-halftone image generation. The basic authentication is performed by examining the color multi-halftone image under a reference illumination and verifying that the message incorporated within the color multi-halftone is hidden and revealed under a different illumination. Authentication can further be performed by observing the color multi-halftone image both in reflection and transmission modes and verifying that in one of these modes the message is hidden and that in the other mode the message is revealed.

Synthesis of authenticable color multi-halftone images

The Yule-Nielsen modified Spectral Neugebauer reflection prediction model enhanced with an ink spreading model provides high accuracy when predicting reflectance spectra from ink surface coverages. In the present contribution, we try to inverse the model, i.e. to deduce the surface coverages of a printed color halftone patch from its measured reflectance spectrum. This process yields good results for cyan, magenta, and yellow inks, but unstable results when simultaneously fitting cyan, magenta, yellow, and black inks due to redundancy between these four inks: black can be obtained by printing either the black ink or similar amounts of the cyan, magenta, and yellow inks. To overcome this problem, we use the fact that the black pigmented ink absorbs light in the infrared domain, whereas cyan, magenta, and yellow inks do not. Therefore, with reflection spectra measurements spanning both the visible and infrared domain, it is possible to accurately deduce the black ink coverage. Since there is no redundancy anymore, the cyan, magenta, yellow, and pigmented black ink coverages can be recovered with high accuracy.

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Model-Based Deduction of CMYK Surface Coverages from Visible and Infrared Spectral Measurements of Halftone Prints

Most existing techniques for regulating the ink flow in offset presses rely oil density measurements carried out oil specially printed patches. In the present contribution. we develop a methodology to deduce ink thickness variations from spectral measurements of multichromatic halftone patches located within the printed page. For this purpose, we extend the Clapper-Yule spectral reflectance prediction model by expressing the transmittance of the colorants composed of superposed inks as a function of the ink transmittances and of fitted ink layer thicknesses. We associate to each ink all ink thickness variation factor. At print time, this ink thickness variation factor can be fitted to minimize a difference metric between predicted reflection spectrum and measured reflection spectrum. The ink thickness variations deduced from multichromatic halftones allow to clearly distinguish between normal ink volume, reduced ink volume, or increased ink volume. This information can then he used for performing control operations on the printing press. (C) 2009 Wiley periodicals, Inc. Col Res Appl, 34, 432-442. 2009; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20541

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Deducing ink thickness variations by a spectral prediction model

The Yule-Nielsen modified spectral Neugebauer model enables predicting reflectance spectra from surface coverages. In order to provide high prediction accuracy, this model is enhanced with an ink spreading model accounting for physical dot gain. Traditionally, physical dot gain, also called mechanical dot gain, is modeled by one ink spreading curve per ink. An ink spreading curve represents the mapping between nominal to effective dot surface coverages when an ink halftone wedge is printed. In previous publications, we have shown that using one ink spreading curve per ink is not sufficient to accurately model physical dot gain, and that the physical dot gain of a specific ink is modified by the presence of other inks. We therefore proposed an ink spreading model taking all the ink superposition conditions into account. We now show that not all superposition conditions are useful and necessary when working with cyan, magenta, yellow, and black inks. We therefore study the influence of ink spreading in different superposition conditions on the accuracy of the spectral prediction model. Finally, we propose new, simplified ink spreading equations that better suit CMYK prints and are more resilient to noise.

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Simplified ink spreading equations for CMYK halftone prints

The Yule-Nielsen modified spectral Neugebauer model (YNSN) enhanced for accounting for ink spreading in the different ink superposition conditions provides accurate spectral predictions, but requires one to measure the reflectances of special halftone calibration patches in order to compute the ink spreading curves mapping nominal ink surface coverage to effective ink surface cov- erage. Printing special halftone calibration patches within the bor- ders of the print pages is cumbersome, since these special patches need to be cut out before assembling the final printed product. In the present contribution, we calibrate the ink spreading curves directly from the printed images by fitting them so as to minimize a distance metric between predicted reflectances and measured reflectances at selected relatively uniform locations. We compare the prediction accuracy of the so-calibrated YNSN model with the prediction accu- racy of the same model calibrated by the spectral reflectances of classical uniform calibration patches. Interestingly, when the model is calibrated from image tiles originating from the same or from a similar color image as the one comprising the test tiles, better pre- diction results are obtained than when performing a classical cali- bration on 50% halftone patches printed in all superposition conditions. © 2009 Society for Imaging Science and Technology. DOI: 10.2352/J.ImagingSci.Technol.2009.53.3.030502

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Thomas Bugnon

Papers

Introducing ink spreading within the cellular Yule-Nielsen modified Neugebauer model

Model-Based Deduction of CMYK Surface Coverages from Visible and Infrared Spectral Measurements of Halftone Prints

Deducing ink thickness variations by a spectral prediction model

Simplified ink spreading equations for CMYK halftone prints

Deducing Ink Spreading Curves from Reflection Spectra Acquired Within Printed Color Images