In halftone-driven imaging pipelines focus is often placed on halftone pattern design as the main contributor to overall output quality. However, for sequential or cumulative imaging technologies, such as multi-pass printing, an important element is also pattern partitioning - how the overall halftone pattern is divided among the different partial imaging events such as printing passes. Partitioning is usually designed agnostically of the halftone pattern, making it impossible to optimize for the joint effect of halftone and partitioning. However, even a good halftone pattern coupled with a good partitioning scheme does not guarantee well partitioned halftones and can impact image quality attributes. In this paper a novel approach called PARAOMASKING is presented that benefits from the pattern-determinism of PARAWACS halftoning and proposes a partitioning scheme for multi-pass printing such that optimality is also obtained for partitioned halftones. Results - both digital and printed - show how it can lead to significant improvements in partial pattern quality and overall pattern quality. Consequently, output attributes such as grain, coalescence and pattern robustness are improved. The focus here is on blue-noise pattern preservation but the approach can also be extended to other objectives, e.g., maximizing per-pass clustering.

Halftoning is a key stage of any printing image processing pipeline. With colorant-channel approaches, a key challenge for matrix-based halftoning is the co-optimization of the matrices used for individual colorants, which becomes increasingly complex and over-constrained as the number of colorants increases. Both choices of screen angles (in clustered-dot cases) or structures, and control over how individual matrices relate to each other and result in over-versus side-by-side printing of the colorants, impose challenging restrictions. The solution presented in this paper relies on the benefits of a halftone area Neugebauer separation pipeline, where local Neugebauer Primary use is specified at each pixel and where halftoning can be performed using a single matrix, regardless of the number of colorants. The provably complete plane dependence of the resulting halftones will be presented among the solution's benefits.

Ink-jet print attributes such as color gamut, grain, and cost are consequences of the materials and printing technology used and of choices made during color management, color separation, and halftoning operation. Traditionally, color separation determines what amounts of the available inks to use for each reproducible color, and halftoning deals with the spatial distribution of inks that also results in the nature of their overprinting. However, using an ink space as a means of communication between color separation and halftoning gives access only to some of the printed patterns that a printing system is capable of and, therefore, only to a reduced range of print attributes. Here, a method, i.e., Halftone Area Neugebauer Separation, is proposed to gain access to all possible printable patterns by specifying relative area coverages of a printing system's Neugebauer primaries instead of only ink amounts. This results in delivering prints with more optimal attributes (e.g., using less ink and giving rise to a larger color gamut) than is possible using current methods.

In this paper we propose that two images are captured of every scene: a normal image and an image captured where a coloured filter is placed in front of the camera. This additional information is then used in solving for colour constancy. The novelty of our approach is not that we add a colour filter (this is an old idea) but in how we use the additional information. In contradistinction to previous work we propose that the dimensionality of the 6 measurements per image pixel remains at 3 (not 6): we do not add a filter to increase the number of degrees of freedom but rather as a way of estimating the illuminant. We say that a filter is chromagenic if the relationship between filtered and unfiltered RGBs varies with and depends strongly on illumination. The canonical chromagenic algorithm works by testing the applicability of pre-computed relations in situ in an image. We extend the chromagenic approach to incorporate knowledge of the gamut of colours we expect to see under a given light and so in effect we make a hybrid gamut mapping + chromagenic algorithm. Experiments validate our approach with chromagenic gamut mapping shown to deliver significantly better constancy than all other algorithms tested.

We present a database of full spatial and spectral resolution images of everyday objects captured with a novel multi-spectral device: the applied spectral imaging Spectracube camera. We summarise the operation of the device and present a study of its spectral accuracy before demonstrating the usefulness of the data set by using it to evaluate different white point correction transforms: transforms which map RGBs under one illuminant to a corresponding set of RGBs under a different light. We find that while the best transforms can often give results close to the results obtained using spectral techniques, the results are both image and illuminant dependent and in a number of cases all transforms tested introduce significant errors.