2,019 research outputs found

    Digital Color Imaging

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    This paper surveys current technology and research in the area of digital color imaging. In order to establish the background and lay down terminology, fundamental concepts of color perception and measurement are first presented us-ing vector-space notation and terminology. Present-day color recording and reproduction systems are reviewed along with the common mathematical models used for representing these devices. Algorithms for processing color images for display and communication are surveyed, and a forecast of research trends is attempted. An extensive bibliography is provided

    Pushing the Limits of 3D Color Printing: Error Diffusion with Translucent Materials

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    Accurate color reproduction is important in many applications of 3D printing, from design prototypes to 3D color copies or portraits. Although full color is available via other technologies, multi-jet printers have greater potential for graphical 3D printing, in terms of reproducing complex appearance properties. However, to date these printers cannot produce full color, and doing so poses substantial technical challenges, from the shear amount of data to the translucency of the available color materials. In this paper, we propose an error diffusion halftoning approach to achieve full color with multi-jet printers, which operates on multiple isosurfaces or layers within the object. We propose a novel traversal algorithm for voxel surfaces, which allows the transfer of existing error diffusion algorithms from 2D printing. The resulting prints faithfully reproduce colors, color gradients and fine-scale details.Comment: 15 pages, 14 figures; includes supplemental figure

    Print engine color management using customer image content

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    The production of quality color prints requires that color accuracy and reproducibility be maintained to within very tight tolerances when transferred to different media. Variations in the printing process commonly produce color shifts that result in poor color reproduction. The primary function of a color management system is maintaining color quality and consistency. Currently these systems are tuned in the factory by printing a large set of test color patches, measuring them, and making necessary adjustments. This time-consuming procedure should be repeated as needed once the printer leaves the factory. In this work, a color management system that compensates for print color shifts in real-time using feedback from an in-line full-width sensor is proposed. Instead of printing test patches, this novel attempt at color management utilizes the output pixels already rendered in production pages, for a continuous printer characterization. The printed pages are scanned in-line and the results are utilized to update the process by which colorimetric image content is translated into engine specific color separations (e.g. CIELAB-\u3eCMYK). The proposed system provides a means to perform automatic printer characterization, by simply printing a set of images that cover the gamut of the printer. Moreover, all of the color conversion features currently utilized in production systems (such as Gray Component Replacement, Gamut Mapping, and Color Smoothing) can be achieved with the proposed system

    Image-Processing Techniques for the Creation of Presentation-Quality Astronomical Images

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    The quality of modern astronomical data, the power of modern computers and the agility of current image-processing software enable the creation of high-quality images in a purely digital form. The combination of these technological advancements has created a new ability to make color astronomical images. And in many ways it has led to a new philosophy towards how to create them. A practical guide is presented on how to generate astronomical images from research data with powerful image-processing programs. These programs use a layering metaphor that allows for an unlimited number of astronomical datasets to be combined in any desired color scheme, creating an immense parameter space to be explored using an iterative approach. Several examples of image creation are presented. A philosophy is also presented on how to use color and composition to create images that simultaneously highlight scientific detail and are aesthetically appealing. This philosophy is necessary because most datasets do not correspond to the wavelength range of sensitivity of the human eye. The use of visual grammar, defined as the elements which affect the interpretation of an image, can maximize the richness and detail in an image while maintaining scientific accuracy. By properly using visual grammar, one can imply qualities that a two-dimensional image intrinsically cannot show, such as depth, motion and energy. In addition, composition can be used to engage viewers and keep them interested for a longer period of time. The use of these techniques can result in a striking image that will effectively convey the science within the image, to scientists and to the public.Comment: 104 pages, 38 figures, submitted to A

    Investigating the Effect of Color Gamut Mapping Quantitatively and Visually

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    With the advent of various color management standards and tools, the print media industry has seen many advancements aimed towards quantitatively and qualitatively acceptable color reproduction. This research attempts to test one of the most fundamental and integral parts of a standard color management workflow, the profile. The gamut mapping techniques implemented by the ICC profiles created using different profiling application programs were tested for their congruity to the theoretical concepts, standards, and definitions documented by International Color Consortium (ICC). Once these profiling software applications were examined, the significance of the possible discrepancies were tested by establishing a visual assessment of pictorial images using these profiles. In short, this research assessed the implementations of the ICC color rendering intents in a standard or a commonly used color managed workflow, and then described the significance of these discrepancies in terms of interoperability. For this research, interoperability was defined the assessment of different ICC profiles in producing similar results, i.e., quantitatively and visually. In order to achieve the desired assessment, the two profiling applications were selected and each used to create an output profile using the same characterization data set. The two profiles were then compared for differences in the way they mapped real world colors. The results displayed that even though there were some significant quantitative color differences, visual subjective evaluation did not reflect any noticeable color differences and therefore concluded that the profiles were interoperable. These findings reveal that even though quantitative color differences may reflect significant color differences, subjective visual comparisons may not always reflect the same or agree with quantitative findings

    Rank-based camera spectral sensitivity estimation

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    In order to accurately predict a digital camera response to spectral stimuli, the spectral sensitivity functions of its sensor need to be known. These functions can be determined by direct measurement in the lab—a difficult and lengthy procedure—or through simple statistical inference. Statistical inference methods are based on the observation that when a camera responds linearly to spectral stimuli, the device spectral sensitivities are linearly related to the camera rgb response values, and so can be found through regression. However, for rendered images, such as the JPEG images taken by a mobile phone, this assumption of linearity is violated. Even small departures from linearity can negatively impact the accuracy of the recovered spectral sensitivities, when a regression method is used. In our work, we develop a novel camera spectral sensitivity estimation technique that can recover the linear device spectral sensitivities from linear images and the effective linear sensitivities from rendered images. According to our method, the rank order of a pair of responses imposes a constraint on the shape of the underlying spectral sensitivity curve (of the sensor). Technically, each rank-pair splits the space where the underlying sensor might lie in two parts (a feasible region and an infeasible region). By intersecting the feasible regions from all the ranked-pairs, we can find a feasible region of sensor space. Experiments demonstrate that using rank orders delivers equal estimation to the prior art. However, the Rank-based method delivers a step-change in estimation performance when the data is not linear and, for the first time, allows for the estimation of the effective sensitivities of devices that may not even have “raw mode.” Experiments validate our method

    The development of methodologies for color printing in digital inkjet textile printing and the application of color knowledge in the Ways of Making Project

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    Digital textile printing (DTP) offers creative potential and entrepreneurial business models in textile design. Designers are no longer restricted to a number of colors or pattern repeat. It has become possible to print fabric without large set-up costs. This relatively sustainable technology reduces water-usage and dye-wastage. DTP meets Just in Time, Concept to Consumer demand, reducing stock wastage. However, there is a marked difference between screen-color to print-color and software allows a user to select colors unprintable using CMYK (cyan, magenta, yellow, black) colorants. Color results are further affected by factors such as structure and composition of the fabric, dye type, printer communications, fabric pre-treatments and secondary processes. A textile designer will be required to understand and experiment with a number of variables in order to feel color-confident. This paper presents investigations which focused on developing methods to aid a designer’s color expectation knowledge, using a Practice-as-Research methodology. Outcomes include a color reference book, digital lap dip tests presented as color maps, and a set of indicator ICC profiles, generated from data accumulated through measuring printed color differences on a variety of substrates. These visual prompts are intended to support designers to build their own internal color look-up table enabling them to predict and resolve color issues during the design process.Finally, the paper concludes by presenting a Case Study detailing an application of these color methods by the researcher for the Ways of Making project, a collaboration between Sir Peter Blake, Worton Hall Studios and Centre for Fine Print Research (CFPR) at University of West of England (UWE). Here, the indicator profiles were applied to Blake’s images, altering the color data to create experimental color modifications and printed onto silk. An initial selection of works from the project were exhibited at London Original Print Fair, Royal Academy, April 2019
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