In this work, we take a microstructure model based approach to the problem of color prediction of halftones created using an inkjet printer. We assume absorption and scattering of light through the colorant layers and model the subsurface light scattering in the substrate by a Gaussian point spread function. We restrict our analysis to transparent substrates. To model the absorption and scattering of light through the colorant layers, we employ the Kubelka-Munk color mixing mode. To model the scattering in the substrate and to predict the spectral distribution, we use a wavelength dependent version of the reflection prediction model developed by Ruckdeschel and Hauser. Using spectral distributions and ink weight measurements for transparencies completely and homogeneously coated with colorants, we compute the absorption and scattering spectra of the colorants using the Kubelka-Munk theory. We train our model using measured spectral distribution and synthesized microstructure images of primary ramps printed on transparent media. For each patch in the primary ramp, we synthesize a high-resolution halftone microstructure image from the halftone bitmap assuming dot profiles with Gaussian roll-offs, form which we compute a high-resolution transmission image using the Kubelka-Munk theory and the absorption and scattering spectra of the colorants. We then convolve this transmission image with the Gaussian point spread function of the transparent substrate to predict the average spectral distribution of the halftone. We use our model to predict the spectral distribution of a secondary ramp printed on the same media.
KEYWORDS: Printing, Halftones, Calibration, RGB color model, CMYK color model, Binary data, Visual process modeling, Algorithm development, Diffusion, Color imaging
In this paper, we develop a model based color halftoning method using the direct binary search (DBS) algorithm. Our method strives to minimize the perceived error between the continuous tone original color image and the color halftone image. We exploit the differences in low human viewers respond to luminance and chrominance information and use the total squared error in a luminance/chrominance based space as our metric. Starting with an initial halftone, we minimize this error metric using the DBS algorithm. Our method also incorporates a measurement based color printer dot interaction model to prevent the artifacts due to dot overlap and to improve color texture quality. We calibrate our halftoning algorithm to ensure accurate colorant distributions in resulting halftones. We present the color halftones which demonstrate the efficacy of our method.
Conference Committee Involvement (6)
Color Imaging XIII: Processing, Hardcopy, and Applications
29 January 2008 | San Jose, California, United States
Color Imaging XII: Processing, Hardcopy, and Applications
30 January 2007 | San Jose, CA, United States
Color Imaging XI: Processing, Hardcopy, and Applications
17 January 2006 | San Jose, California, United States
Color Imaging X: Processing, Hardcopy, and Applications
17 January 2005 | San Jose, California, United States
Color Imaging IX: Processing, Hardcopy, and Applications IX
20 January 2004 | San Jose, California, United States
Color Imaging VIII: Processing, Hardcopy, and Applications
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