Sampling Optimization for Printer Characterization by Greedy Search

Morovič, Ján; Arnabat, Jordi; Richard, Yvan; Albarrán, Ángel

doi:10.1109/tip.2010.2050111

Cited by 8 publications

(5 citation statements)

References 4 publications

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“…However, in that contribution more than 10,000 colour samples were printed and measured, which is definitely impractical for daily applications. Therefore, several researchers have focused on reducing the amount of modelling samples while maintaining an acceptable precision by using some nonuniformly sampling approaches [29,30]. Unfortunately, it is not easy to apply those nonuniform sampling methods into CYNSN models due to their cellular structures, which actually raise challenges for related studies.…”

Section: Introductionmentioning

confidence: 99%

Optimizing the Spectral Characterisation of a CMYK Printer with Embedded CMY Printer Modelling

et al. 2019

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In the digital printing process, reliable colour reproduction is commonly achieved by printer characterisation, which defines the correspondence between the input device control values and the output colour information. The cellular Yule–Nielsen spectral Neugebauer model, together with its variants, is widely adopted in this topic because of its superb colorimetric and spectral accuracy. However, it seems that current studies have neglected an inconspicuous defect in such models when characterising printers equipped with black ink. That is, the cellular structure of these models overemphasises the sampling for dark-tone colours, and thus leads to relatively large errors in light tones. In this paper, taking a CMYK printer as an example, a simple and effective solution is proposed with no need of extra sampling. With the aid of a newly built cellular spectral Neugebauer model for the embedded CMY printer, this approach optimises the printer characterisation for light tones, slightly improves the precision for middle tones while it maintains the accuracy for dark tones. The performance of the proposed method was evaluated with regard to three different kinds of substrates and the experimental results validated its improvement in spectral printer characterisation.

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Section: Introductionmentioning

confidence: 99%

Optimizing the Spectral Characterisation of a CMYK Printer with Embedded CMY Printer Modelling

et al. 2019

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“…There are mainly two approaches for printer characterization. The first one is a black-box approach relying on color measurements of printed samples and on interpolation to create relationships between colors and amounts of inks [8]. The second approach relies on spectral prediction models that account for the interaction of light, paper and ink halftones [9].…”

Section: Introductionmentioning

confidence: 99%

<inline-formula> <tex-math notation="LaTeX">$N$ </tex-math> </inline-formula>-Ink Printer Characterization With Barycentric Subdivision

Babaei

Hersch

2016

IEEE Trans. on Image Process.

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Abstract-Printing with a large number of inks, also called N-ink printing, is a challenging task. The challenges comprise spectral modelling of the printer, color separation, halftoning, and limitations of the amount of inks. Juxtaposed halftoning, a perfectly dot-off-dot halftoning method, has proven to be useful to address some of these challenges. However, for juxtaposed halftones, prediction of colors as a function of ink area-coverages has not yet been fully investigated. The goal of this paper is to introduce a spectral prediction model for N-ink juxtaposed-halftone prints. As the area-coverage domain of juxtaposed inks forms a simplex, we propose a cellular subdivision of the area-coverage domain using barycentric subdivision of simplexes.The barycentric subdivision provides algorithmically straightforward means to design and implement an N-ink color prediction model. Within the subdomain cells, the Yule-Nielsen spectral Neugebauer model is used for the spectral prediction. Our proposed model is highly accurate for prints with a large number of inks while requiring a relatively low number of calibration samples.

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“…[2] This paper mainly focuses on the former process. Many mathematical models have been employed during color characterization, such as the spectral Neugebauer equations, [3,4] Kubelka-Munk model, [5] polynomial functions based on least-squares, [6,7] artificial neural networks (ANNs), [8,9] 3D interpolation techniques, [10][11][12][13] and so on. Spectral Neugebauer equations are established based on subtractive coloring principle and widely used for color characterization.…”

Section: Introductionmentioning

confidence: 99%

“…While for the midpoint c ¼ 25%, the normalized theoretical value is c 0 ¼ 50% and its effective area coverage c 0 eff;0:5 can be calculated by using Eq. [10]. With all the normalized area coverage and corresponding effective values, the three points can be expressed as (0,0), (0.5, c 0 eff;0:5 ), and (1, 1).…”

mentioning

confidence: 99%

Modified Spectral Neugebauer Model for Printer Characterization

Sun

Liu

Zhou

et al. 2015

Spectroscopy Letters

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Spectral Neugebauer model is widely used for spectral reflectance prediction during printer characterization. However, several factors reduce the predication precision. Thus, an improved cellular Yule-Nielson spectral Neugebauer (CYNSN) model is proposed, which modifies the traditional spectral Neugebauer model in three main aspects: (1) First, in order to adjust the nonlinearities between the predicated and measured spectral reflectance, an iteratively calculated Yule-Nielson exponent is added to the reflectance values within the Neugebauer equations.(2) Second, the quantity of Neugebauer primaries is increased by dividing the CMY colorant space into 4 3 uniform cellular subdomains. (3) Third, the mapping functions are developed to map the area coverages' theoretical values to their effective values within the subdomains, and the mapped values highly improve the matching degree of the predicated and measured reflectance values. In the experiment, four related spectral Neugebauer models are employed during printer characterization, which are the traditional spectral Neugebauer model, Yule-Nielson spectral Neugebauer (YNSN) model, traditional CYNSN model, and the modified CYNSN model, respectively. And the experimental results show the modified CYNSN model yields a significant improvement over the other spectral Neugebauer models, by comparing the characterization errors in the form of colorimetry and spectroscopy.

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Sampling Optimization for Printer Characterization by Greedy Search

Cited by 8 publications

References 4 publications

Optimizing the Spectral Characterisation of a CMYK Printer with Embedded CMY Printer Modelling

Optimizing the Spectral Characterisation of a CMYK Printer with Embedded CMY Printer Modelling

<inline-formula> <tex-math notation="LaTeX">$N$ </tex-math> </inline-formula>-Ink Printer Characterization With Barycentric Subdivision

Modified Spectral Neugebauer Model for Printer Characterization

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