To achieve the best image quality, noise and artifacts are generally removed at the cost of a loss of details generating the
blur effect. To control and quantify the emergence of the blur effect, blur metrics have already been proposed in the
literature. By associating the blur effect with the edge spreading, these metrics are sensitive not only to the threshold
choice to classify the edge, but also to the presence of noise which can mislead the edge detection.
Based on the observation that we have difficulties to perceive differences between a blurred image and the same reblurred
image, we propose a new approach which is not based on transient characteristics but on the discrimination
between different levels of blur perceptible on the same picture.
Using subjective tests and psychophysics functions, we validate our blur perception theory for a set of pictures which
are naturally unsharp or more or less blurred through one or two-dimensional low-pass filters. Those tests show the
robustness and the ability of the metric to evaluate not only the blur introduced by a restoration processing but also focal
blur or motion blur. Requiring no reference and a low cost implementation, this new perceptual blur metric is applicable
in a large domain from a simple metric to a means to fine-tune artifacts corrections.
The proposed new spectral reflection model enhances the classical Clapper-Yule model by taking into account the fact that proportionally more incident light through a given colorant surface is reflected back onto the same colorant surface than onto other colorant surfaces. It comprises a weighted mean between a component specifying the part of the incident light that exits through the same colorant as the colorant from which it enters (Saunderson corrected Neugebauer component) and a component specifying the part of the incident light whose emerging light components exit from all colorants (Clapper-Yule component). We also propose models for taking into account ink spreading, a phenomenon that occurs when printing an ink halftone in superposition with one or several solid inks. The ink-spreading model incorporates nominal-to-effective surface coverage functions for each of the different ink superposition conditions. A system of equations yields the effective ink surface coverages of a color halftone as a weighted mean of the ink surface coverages specific to the different superposition conditions. The new spectral reflection prediction model combined with the ink-spreading model yields excellent spectral reflection predictions for clustered-dot color halftones printed on an offset press or on thermal transfer printers.
Dot gain is different when dots are printed alone, printed in superposition with one ink or printed in superposition with two inks. In addition, the dot gain may also differ depending on which solid ink the considered halftone layer is superposed. In a previous research project, we developed a model for computing the effective surface coverage of a dot according to its superposition conditions. In the present contribution, we improve the Yule-Nielsen modified Neugebauer model by integrating into it our effective dot surface coverage computation model. Calibration of the reproduction curves mapping nominal to effective surface coverages in every superposition condition is carried out by fitting effective dot surfaces which minimize the sum of square differences between the measured reflection density spectra and reflection density spectra predicted according to the Yule-Nielsen modified Neugebauer model. In order to predict the reflection spectrum of a patch, its known nominal surface coverage values are converted into effective coverage values by weighting the contributions from different reproduction curves according to the weights of the contributing superposition conditions. We analyze the colorimetric prediction improvement brought by our extended dot surface coverage model for clustered-dot offset prints, thermal transfer prints and ink-jet prints. The color differences induced by the differences between measured reflection spectra and reflection spectra predicted according to the new dot surface estimation model are quantified on 729 different cyan, magenta, yellow patches covering the full color gamut. As a reference, these differences are also computed for the classical Yule-Nielsen modified spectral Neugebauer model incorporating a single halftone reproduction curve for each ink. Taking into account dot surface coverages according to different superposition conditions considerably improves the predictions of the Yule-Nielsen modified Neugebauer model. In the case of offset prints, the mean difference between predictions and measurements expressed in CIE-LAB CIE-94 ΔE<sub>94</sub> values is reduced at 100 lpi from 1.54 to 0.90 (accuracy improvement factor: 1.7) and at 150 lpi it is reduced from 1.87 to 1.00 (accuracy improvement factor: 1.8). Similar improvements have been observed for a thermal transfer printer at 600 dpi, at lineatures of 50 and 75 lpi. In the case of an ink-jet printer at 600 dpi, the mean ΔE<sub>94</sub> value is reduced at 75 lpi from 3.03 to 0.90 (accuracy improvement factor: 3.4) and at 100 lpi from 3.08 to 0.91 (accuracy improvement factor: 3.4).
We propose a new spectral prediction model as well as new approaches for modeling ink spreading which occurs when printing ink layer superpositions. The spectral prediction model enhances the classical Clapper-Yule model by taking into account the fact that proportionally more incident light through a given colorant surface is reflected back onto the same colorant surface than onto other colorant surfaces. This is expressed by a weighted mean between a component specifying the part of the incident light which exits through the same colorant as the colorant from which it enters (Saunderson corrected Neugebauer component) and a component specifying the part of the incident light whose emerging light components exit from all colorants, with a probability to exit from a given colorant equal to that colorant surface coverage (Clapper-Yule component). We also propose two models for taking into account ink spreading, a phenomenon which occurs when printing an ink halftone in superposition with one or several solid inks. Besides the physical dot gain present within a single ink halftone print, we consider in the first model the ink spreading which occurs when an ink halftone is printed on top of one or two solid inks. In the second more advanced model, we generalize this concept to ink halftones printed on top or below solid inks. We formulate for both ink spreading models systems of equations which allow to compute effective ink coverages as a combination of the individual ink coverages which occur in the different superposition cases. The new spectral prediction model combined with advanced ink spreading yields excellent spectral predictions for clustered-dot color halftone prints, both in the case of offset (75 to 150 lpi) and in the case of thermal transfer printers (50 to 75 lpi).