Color Reproduction of Metallic-Ink Images

Abstract

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.

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

“…As halftone visibility, graininess can also be used to describe the result of local density variations of an overall uniform area (Babaei and Hersch, 2016a). Graininess not only depends on halftone visibility, but also on the color separation method, and hence on the number and type of inks present in the print.…”

“…Even though the standard deviation of S-CIEL* is used as a metric for halftone visibility in Son et al (2011) and Babaei and Hersch (2016a), it is interesting to see its tendencies over color printed and scanned patches. This metric has therefore been included in the evaluation.…”

“…based on different quality criteria (Agar, 2001, Taplin and Berns, 2001, Chen et al, 2004, Jang et al, 2006b, Chen et al, 2008, Urban and Berns, 2011, Jewell et al, 2013, Babaei and Hersch, 2016a. The regular inverse model finds the ink combination giving the smallest colorimetric difference to the target color (Taplin and Berns, 2001, Chen et al, 2004, Jang et al, 2006b, Urban and Berns, 2011.…”

“…They also impose limitations on the dot size, favoring ink combinations that avoid very high ink coverages (deep shadows) or very low coverages (low highlights). Babaei and Hersch (2016a) perform the color separation based on halftone dot visibility and smoothness across subgamuts. Chen et al (2008) perform the color separation to 6-channel printing with colorimetric similarity across different illuminants and perceptual image quality, i.e.…”

“…Four main challenges are identified and addressed: 1) employing 11 inks potentially increases the complexity of color characterization, 2) control over the ink overlap between 11 ink combinations needs to be achieved to avoid over-inking, 3) the secondary color inks potentially result in high graininess at low area coverages, and 4) the conversion from the 3-dimensional CIELAB color space to multi-channel ink coverages in the inverse model constitutes a one-to-many mapping problem. Several color separation approaches for multi-channel printing exist in literature (Boll, 1994, Tzeng and Berns, 2000, Chen et al, 2004, 2008, Urban and Berns, 2011, Jewell et al, 2013, Deshpande et al, 2014a, Le Moan and Urban, 2014, Babaei and Hersch, 2016a. The color separation presented in this chapter deals with these challenges by distincting itself from the separations methods found in literature by: 1) the separation is performed using both light inks 119 7.…”