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

Hébert, Mathieu; Hersch, Roger D.

doi:10.1002/col.21907

Cited by 38 publications

(38 citation statements)

References 25 publications

(28 reference statements)

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“…They rely on the statistically independent superposition of ink dots. 25 We can verify that the sum of all area coverages in the Demichel formulas is 1. Note that using the Demichel pseudo-ink to colorant separation formulas does not imply that the colorants should be laid out independently.…”

Section: Demichel's Ink-to-colorant Separation Formulasmentioning

confidence: 88%

Color Reproduction of Metallic-Ink Images

Babaei¹,

Hersch²

2016

jist

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Abstract. We study the color reproduction of full-color metallic-ink images. Full-color metallic-ink images are prints whose contributing colorants are exclusively made of colored metallic inks. Due to the presence of metallic particles, metallic inks show a metal-like luster. These particles are opaque and hide the underlying ink or substrate. In order to obtain predictable halftone colors, we need a juxtaposed halftoning method to create halftone dots of different colors side by side without overlapping. Juxtaposed halftoning invalidates many assumptions generally made for the color-reproduction workflow. For printing metallic-ink images, one needs a color-separation system creating surface coverages for the eight metallic inks that correspond to the eight Neugebauer primaries. For this purpose, we introduce a simple and fast method for N-color separation that relies either on Demichel's or on a variant of Kueppers' ink-to-colorant separations. Thanks to a unique set of ink-to-colorant formulas, pseudo-CMY ink values are separated into amounts of printable colorants. We also describe color-separation procedures that are able to optimize different properties of the resulting metallic-ink images. INTRODUCTIONA common element present in all printing applications is the color-reproduction workflow. A color-reproduction workflow converts an input image into the printer's command language. 1 Most existing reproduction workflows follow the steps shown in Figure 1. Briefly, input colors are first converted from a source color space, such as sRGB, into a device-independent color space such as CIELAB. 2 By performing gamut mapping, 3 the input colors are mapped into the colors of the usually narrower print gamut. Then, the color separation is carried out by converting the gamut-mapped printable colors into amounts of printer inks. The separated ink layers are then halftoned and printed.We can use a spectral prediction model for color separation and gamut mapping. The forward prediction model expresses the forward characterization. It determines the printer's color response to input control values, e.g. the amount of inks to be printed. By varying the amount of inks in the forward model, we can determine the color gamut of a printer. The spectral prediction model is also required in inverse mode for the color separation in order to deduce the amounts of inks that are needed to print a specific color.

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Section: Demichel's Ink-to-colorant Separation Formulasmentioning

confidence: 88%

Color Reproduction of Metallic-Ink Images

Babaei¹,

Hersch²

2016

jist

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“…The Neugebauer model predicts the CIEXYZ-color of a given halftone by convex interpolation of the CIEXYZ colors of all participating colorants. Assuming that halftone screen dots of different ink layers are laid out independently one from another, which is an acceptable assumption for classic halftoning methods [14,15], printing N superposed ink-layers yields 2 N possible colorants whose area coverages can be computed by Demichel equations [9,15,16]. In the case of a classic CMY print, the halftone is composed of the 8 colorants, also known as the Neugebauer primaries: white, cyan, magenta, yellow, blue, green, red and black.…”

Section: A Yule-nielsen Spectral Neugebauer Model and Its Variantsmentioning

confidence: 99%

“…Such a model is known as independent ink-spreading model. Hersch and Crété [19] developed a general ink-spreading model that accounts for different superposition conditions, called the superposition-dependent ink-spreading model [9].…”

Section: A Yule-nielsen Spectral Neugebauer Model and Its Variantsmentioning

confidence: 99%

“…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]. The parameters of the spectral prediction models are usually derived from the calibration set, a set of measured color samples.…”

Section: Introductionmentioning

confidence: 99%

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<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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“…The cellular Yule-Nielsen modified Neugebauer model (cYNMN), introduced in Heuberger et al (1992), is an extension of the YNMN model for improved precision (Hébert and Hersch, 2015) in which, in addition to the reflectance of no ink and full coverage ink combinations, additional reflectance values serve as input to the formula (Heuberger et al, 1992, Rolleston andBalasubramanian, 1993 …”

Section: Cellular Yule-nielsen Modified Neugebauer Modelmentioning

confidence: 99%

Improving image quality in multi-channel printing - multilevel halftoning, color separation and graininess characterization

Elias¹

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Color printing is traditionally achieved by separating an input image into four channels (CMYK) and binarizing them using halftoning algorithms, in order to designate the locations of ink droplet placement. Multi-channel printing means a reproduction that employs additional inks other than these four in order to augment the color gamut (scope of reproducible colors) and reduce undesirable ink droplet visibility, so-called graininess.One aim of this dissertation has been to characterize a print setup in which both the primary inks CMYK and their light versions are used.The presented approach groups the inks, forming subsets, each representing a channel that is reproduced with multiple inks. To halftone the separated channels in the present methodology, a specific multilevel halftoning algorithm is employed, halftoning each channel to multiple levels. This algorithm performs the binarization from the ink subsets to each separate colorant. Consequently, the print characterization complexity remains unaltered when employing the light inks, avoiding the normal increase in computational complexity, the one-to-many mapping problem and the increase in the number of training samples. The results show that the reproduction is visually improved in terms of graininess and detail enhancement.The secondary color inks RGB are added in multi-channel printing to increase the color gamut. Utilizing them, however, potentially increases v the perceived graininess. Moreover, employing the primary, secondary and light inks means a color separation from a three-channel CIELAB space into a multi-channel colorant space, resulting in colorimetric redundancy in which multiple ink combinations can reproduce the same target color. To address this, a proposed cost function is incorporated in the color separation approach, weighting selected factors that influence the reproduced image quality, i.e. graininess and color accuracy, in order to select the optimal ink combination. The perceived graininess is modeled by employing S-CIELAB, a spatial low-pass filtering mimicking the human visual system. By applying the filtering to a large dataset, a generalized prediction that quantifies the perceived graininess is carried out and incorporated as a criterion in the color separation.Consequently, the presented research increases the understanding of color reproduction and image quality in multi-channel printing, provides concrete solutions to challenges in the practical implementation, and rises the possibilities to fully utilize the potential in multi-channel printing for superior image quality.

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

Cited by 38 publications

References 25 publications

Color Reproduction of Metallic-Ink Images

Color Reproduction of Metallic-Ink Images

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

Improving image quality in multi-channel printing - multilevel halftoning, color separation and graininess characterization

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