An important aspect for print quality assessment is the perceived gloss level across the printout. There exists a strong relationship between the surface roughness of a printout and the amount of specular reflection which is perceived as gloss variations. Different print parameters influence the surface roughness of the printouts such as the paper substrate, the type of inks and the print method. The lack of control over the print's surface roughness may result in artifacts such as bronzing and differential gloss. Employing a 2.5D or relief printing system, we are able to control the printout roughness by manipulating the way the ink is deposited in a layer-by-layer basis. By changing the deposition time in between two layers of white ink and the order on which the pixels are printed, we achieve different gloss levels from a matte to a glossy appearance that can be controlled locally. Understanding the relationship between different printing parameters and the resulting gloss level allows us: to solve differential gloss artifacts (to obtain a print with a full gloss or matte finish) and to use the local gloss variations to create reflection effects in the printouts. Applications related to security printing have also been explored. Our results showed a reduced level of gloss toward a matte appearance as the ink deposition time between the layers was increased, allowing more time for the ink to dry between passes. We measured the gloss levels using a gloss meter and a psychophysical experiment was conducted to validate our measurements and observations
Spectral printing aims to achieve an illuminant-invariant match between the original and the reproduction. Due to limited printer spectral gamuts, an errorless spectral reproduction is mostly impossible, and spectral gamut mapping is required to reduce perceptual errors. The recently proposed paramermismatch-based spectral gamut mapping (PMSGM) strategy minimizes such errors. However, due to its pixel-wise processing, it may result in severely different tonal values for spectrally similar adjacent pixels, causing unwanted edges (banding) in the final printout. While the addition of some noise to the a* and b* channels of the colorimetric (e.g., CIELAB) image-rendered for the first illuminant-prior to gamut mapping solves the banding problem, it adversely increases the image graininess. In this article, the authors combine the PMSGM strategy with subsequent spectral separation, considering the spatial neighborhood within the tonal-value space and the illuminant-dependent perceptual spaces to directly compute tonal values. Their results show significant improvements to the PMSGM method in terms of avoiding banding artifacts.
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