Six-color separation for improving graininess in a middle tone region

Son, Chang-Hwan; Kim, Yun-Tae; Lee, Cheol-Hee; Ha, Yeong-Ho

doi:10.1117/12.526261

Cited by 8 publications

(7 citation statements)

References 1 publication

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“…Naturally, the graininess differs not only according to the ink coverage and number of levels, but also in relation to the contrast of the ink to the paper -for instance, the graininess of 50% yellow ink coverage will be different than that of 50% black ink coverage. Son et al (2003Son et al ( , 2006 …”

Section: Standard Deviation Of Digital Halftonesmentioning

confidence: 99%

“…When the additional colorants in multi-channel printing are the lighter versions of the primary inks, the color separation problem has previously been tackled by introducing an in-between step, where colorants are separated into four channels first and then to multi-channel (Noyes et al, 2000, Agar, 2001, Agar et al, 2002, Son et al, 2003, Jang et al, 2006a, Son et al, 2011.…”

Section: Previous Workmentioning

confidence: 99%

“…Meanwhile, Son et al (2003Son et al ( , 2006 and Son et al (2011) utilize granularity metrics in order to achieve a six-channel separation employing lighter inks. The separation was performed using colorimetric data in Son et al (2003) and Son et al (2006), and spectral data in Son et al (2011).…”

Section: Previous Workmentioning

confidence: 99%

“…The standard deviation of the color fluctuations of halftones, passed through S-CIELAB filtering, has been used as a graininess metric (Son et al, 2003, 2006, Ortiz Segovia et al, 2012.…”

Section: Graininessmentioning

confidence: 99%

“…The separation was performed using colorimetric data in Son et al (2003) and Son et al (2006), and spectral data in Son et al (2011).…”

Section: Previous Workmentioning

confidence: 99%

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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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Section: Standard Deviation Of Digital Halftonesmentioning

confidence: 99%

Section: Previous Workmentioning

confidence: 99%

Section: Previous Workmentioning

confidence: 99%

“…The standard deviation of the color fluctuations of halftones, passed through S-CIELAB filtering, has been used as a graininess metric (Son et al, 2003, 2006, Ortiz Segovia et al, 2012.…”

Section: Graininessmentioning

confidence: 99%

“…The separation was performed using colorimetric data in Son et al (2003) and Son et al (2006), and spectral data in Son et al (2011).…”

Section: Previous Workmentioning

confidence: 99%

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

Elias¹

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Color separation for improved perceived image quality in terms of graininess and gamut

Elias

Nyström

Gooran

2016

Color Research & Application

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Multi‐channel printing employs additional inks to improve the perceived image quality by reducing the graininess and augmenting the printer gamut. It also requires a color separation that deals with the one‐to‐many mapping problem imposed when using more than three inks. The proposed separation model incorporates a multilevel halftoning algorithm, reducing the complexity of the print characterization by grouping inks of similar hues in the same channel. In addition, a cost function is proposed that weights selected factors influencing the print and perceived image quality, namely color accuracy, graininess and ink consumption. The graininess perception is qualitatively assessed using S‐CIELAB, a spatial low‐pass filtering mimicking the human visual system. By applying it to a large set of samples, a generalized prediction quantifying the perceived graininess is carried out and incorporated as a criterion in the color separation. The results of the proposed model are compared with the separation giving the best colorimetric match, showing improvements in the perceived image quality in terms of graininess at a small cost of color accuracy and ink consumption. © 2016 Wiley Periodicals, Inc. Col Res Appl, 42, 486–497, 2017

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Environment parameters extraction using intelligent image processing system for efficient autonomous driving of a vehicle

Nayagam,

Mariappan,

Babu

et al. 2023

SUSTAINABLE DEVELOPMENTS IN MATERIALS SCIENCE, TECHNOLOGY AND ENGINEERING: Sustainable Development in Material Science of Today

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Six-color separation for improving graininess in a middle tone region

Cited by 8 publications

References 1 publication

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

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

Color separation for improved perceived image quality in terms of graininess and gamut

Environment parameters extraction using intelligent image processing system for efficient autonomous driving of a vehicle

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