To achieve stereoscopy on surround displays interference filters have some advantages over other techniques. However
these filters introduce strong color differences between the projectors, which may reveal that the display is compound by
multiple projectors. This article presents methods for a computationally efficient correction of the colorimetric properties
of multi-projector surround displays. This correction is based on automated measurements by multiple cameras and a
spectrometer.
The described methods were validated by applying them to a stereoscopic dome display made up of 16 high definition
projectors equipped with Infitec filters. On that display we achieved a significant improvement of the colorimetric
properties compared to regular soft-edge blending. Our reference setup shows that the multi-projector approach
combined with interference filters allows to build highly immersive stereoscopic surround displays fulfilling today's
requirements on spatial resolution, frame rates and interaction latencies.
KEYWORDS: Printing, CMYK color model, Spectral models, Inkjet technology, Nonimpact printing, Reflectivity, Performance modeling, Opacity, Color difference, RGB color model
In the context of spectral color image reproduction by multi-channel inkjet printing a key challenge is to accurately
model the colorimetric and spectral behavior of the printer. A common approach for this modeling is to assume that the
resulting spectral reflectance of a certain ink combination can be modeled as a convex combination of the so-called
Neugebauer Primaries (NPs); this is known as the Neugebauer Model. Several extensions of this model exist, such as the
Yule-Nielsen Modified Spectral Neugebauer (YNSN) model. However, as the number of primaries increases, the
number of NPs increases exponentially; this poses a practical problem for multi-channel spectral reproduction.
In this work, the well known Kubelka-Munk theory is used to estimate the spectral reflectances of the Neugebauer
Primaries instead of printing and measuring them, and subsequently we use these estimated NPs as the basis of our
printer modeling. We have evaluated this approach experimentally on several different paper types and on the HP
Deskjet 1220C CMYK inkjet printer and the Xerox Phaser 7760 CMYK laser printer, using both the conventional
spectral Neugebauer model and the YNSN model. We have also investigated a hybrid model with mixed NPs, half
measured and half estimated.
Using this approach we find that we achieve not only cheap and less time consuming model establishment, but also,
somewhat unexpectedly, improved model precision over the models using the real measurements of the NPs.
We aim to print spectral images using spectral vector error diffusion. Vector error diffusion produces good quality
halftoned images but it is very slow to diffuse the error in the image during the halftoning process due to error
accumulation. In spectral images each pixel is a re.ectance and the accumulation of error can modify completly
the shape of the reflectance. This phenomena is increased when data are out of the gamut of the printer. To
control the diffusion of error and to decrease the slowness of the spectral vector error diffusion we preprocess the
spectral image by applying spectral gamut mapping and test the shape of the reflectances by keeping them in a
range of feasible values. Our spectral gamut mapping is based on the inversion of the spectral Neugebauer printer
model. After preprocessing the spectral image to be halftoned is the closest estimation the printer can made
of it with the available colorants. We apply spectral vector error diffusion to spectral images and we evaluate
the halftoning by simulation. We use a seven channels printer which we assume has stable inks and no dot gain
(with a large set of inks we increase the variability or re.ectances the printer can produce). Our preprocessing
and error control have shown promising results.
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