We studied the individual variability of asymmetric metameric colour matching between computer displays and object colour stimuli in conditions typical for the surface colour industries. Using two different computational techniques, we assessed the contribution of observer metamerism to this variability. In the studied conditions of spatially separated computer display and surface colour stimuli, this contribution was found to be insignificant for all colours but neutrals. In the chromaticness plane, the range of matches made by different observers practically coincides with the range of matches made by an individual observer. Consequently, we conclude that in the task of matching spatially separated display and surface colours, the range of matches made by a group of observers cannot be determined from variations in their colour-matching functions, and thus the paradigm of the Standard Deviate Observer is shown to be inapplicable to the studied conditions. We suggest that individual variability in these conditions is governed by mechanisms of chromatic discrimination, and can be modeled by advanced colour difference formulae with suitably adjusted parametric coefficients.
In an asymmetric colour matching experiment, eleven observers adjusted computer displays to colourmatch surface samples in a viewing booth. We found systematic discrepancies between the observers' judgments and the predictions of the CIE 1964 Standard Colorimetric Observer. The features of the discrepancies are consistent with previous reports on adaptation in colour matching and on failures of colorimetric additivity, but have never been confirmed to be significant in practical colorimetry. We attribute the discrepancies to post-receptoral adaptation mainly of the blue-yellow chromatic channel, and report a framework of an adaptation transform based on the MacLeod-Boynton chromaticity diagram which can compensate for them without abandoning traditional colorimetry and the use of tristimulus values.
Figure 1: In preparing an image for print (left), we reduce ink usage by detecting areas which are active (middle, brighter is more active) i.e. contain detailed textures, edges and structure. In these areas we are able to use less cyan, magenta and yellow ink while increasing use of black ink. We are able to reduce ink usage (right) by up to 25% (10% in this example) without degradation in printed image quality.
AbstractA vast majority of color transformations applied to an image in the digital press industry are static and precalculated. In order to achieve the best quality on a wide variety of different images, these transformations tend to be highly conservative with respect to the use of black ink. This results in excessive use of inks, which has a negative economic and environmental impact. We present a method for dynamic computation of color transformation based on image content, with the aim to reduce ink usage. We analyze the image, and predict areas in which quality artifacts that may result from such a reduction will be masked by the image content. These areas include detailed textures, noisy areas and structure. We then replace the image CMYK values by a new combination with increased black. Our algorithm ensures negligible color shifts in the resulting image, and no visible reduction in quality. We achieve an average of over 10% ink savings.
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