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Volume: 26 | Article ID: art00068
Halftone structure optimization using convex programming
  DOI :  10.2352/ISSN.2169-2629.2018.26.410  Published OnlineNovember 2018

In a color printing pipeline, the overall properties of a printed pattern depend on how the available inks are used to reproduce a given color. These choices are typically made in ink-space and therifore concern only how much of each ink to use, with halftoning then determining how those ink amounts interact with each other. For a HANS (Halftone Area Neugebauer Separation) pipeline, it is already the color separation – the recipes of how inks are usedfor a given color – that determines not only ink amounts but also how to combine them, while halftoning only provides their spatial distribution. Hence, with HANS, halftone properties are to a larger extent determined already by the color separation. This is an important change from traditional pipelines and requires different methods of control. This paper describes an approach to achieving new levels of image quality performance, without incurring complexity in the pipeline. It is based on the realization that certain strategies of halftone composition result in less grainy prints, e.g., when minimizing the amount of blank substrate, and more generally minimizing contrast among constituent, at-pixel drop-states (ink combinations). This is achieved through the mathematical technique of convex optimization, where such strategies can beformulated and efficiently computed Results are shown for node-by-node LUT optimization; calibrating LUTs from ink-channel ratio data; transforming LUTs to take into account changes in drop-sequences, sets of admissible NPs or the number of possible NPs to use in an on-line pipeline and generating color samples that match in color but vary in grain. This approach is deeply embedded in the first HANS commercial product, the HP DesignJet Z6 and Z9+ series, a portfolio of pro-photo/graphics printers.

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"Halftone structure optimization using convex programmingin Proc. IS&T 26th Color and Imaging Conf.,  2018,  pp 410 - 416,

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