Spectral printing of paintings using a seven-color digital press

The human visual system is trichromatic and therefore reduces higher dimensional spectral data to three dimensions. Two stimuli with different spectral power curve shapes can result in the same cone response and therefore match each other. Color reproduction systems take advantage of this effect and match color by creating the same cone response as the original but with different colorants. ICC color management transforms all colors into a three-dimensional reference color space, which is independent from any input or output devices. This concept works well for a single defined observer and illumination conditions, but in practice, it is not possible to control viewing conditions leading to severe color mismatches, particularly for paintings. Paintings pose unique challenges because of the large variety of available colorants resulting in a very large color gamut and considerable spectral variability. This research explored spectral color reproduction using a seven-color electrophotographic printing process, the HP Indigo 7000. Because of the restriction to seven inks from the 12 basic inks supplied with the press, the research identified both the optimal seven inks and a set of eight artist paints which can be spectrally reproduced. The set of inks was Cyan, Magenta, Yellow, Black, Reflex Blue, Violet and Orange. The eight paints were Cadmium Red Medium, Cadmium Orange, Cadmium Yellow Light, Dioxazine Purple, Phthalo Blue Green Shade, Ultramarine Blue, Quinacridone Crimson and Carbon Black. The selection was based on both theoretical and experimental analyses. The final testing was computational indicating the possibility of both spectral and colorimetric color reproduction of paintings

Spectral modeling of a six-color inkjet printer

After customizing an Epson Stylus Photo 1200 by adding a continuous-feed ink system and a cyan, magenta, yellow, black, orange and green ink set, a series of research tasks were carried out to build a full spectral model of the printers output. First, various forward printer models were tested using the fifteen two color combinations of the printer. Yule- Nielsen-spectral-Neugebauer (YNSN) was selected as the forward model and its accuracy tested throughout the colorant space. It was found to be highly accurate, performing as well as a more complex local, cellular version. Next, the performance of nonlinear optimization-routine algorithms were evaluated for their ability to efficiently invert the YNSN model. A quasi-Newton based algorithm designed by Davidon, Fletcher and Powell (DFP) was found to give the best performance when combined with starting values produced from the non-negative least squares fit of single-constant Kubelka- Munk. The accuracy of the inverse model was tested and different optimization objective functions were evaluated. A multistage objective function based on minimizing spectral RMS error and then colorimetric error was found to give highly accurate matches with low metameric potential. Finally, the relationship between the number of printing inks and the ability to eliminate metamerism was explored

Developing a spectral and colorimetric database of artist paint materials

As the project of the author\u27s Master\u27s thesis, the development of a spectral and colorimetric database of artist paint materials for acrylic paints was started. The goal of this research project was to: - provide the academic resource of colorant spectral characteristics - give scientifc explanations on various paint-particular phenomena (paint mixing, gloss effects and color gamut expansion by varnishing) These tasks were planned to satisfy possible interests on paint research from not only conservators in museums but also color educators in schools and color reproduction engineers in imaging companies

Assessing the capacity of two-flux models to predict the spectral properties of layered materials

International audienceA classical way of coloring a surface in order to create a still image is the application of a colored coating. The more recent digital printing systems enable depositing thick coatings or successive ink layers. The color rendering of the surface depends on the optical properties of the coated materials (optical index, spectral scattering and absorption coefficients) and their thickness. In order to predict its spectral reflectance as a function of these parameters, the so-called two-flux approach is to be tested in first since the model is simple and relies on analytical equations. It has a good chance to provide accurate predictions for coatings made of solid layers of strongly scattering or nonscattering media, or even complex stratified coatings obtained by stacking nonsymmetrical components such as printed films. The generalized Kubelka-Munk model summarized in this paper enables treating all these configurations with a unified mathematical formalism. But it has limitations and may provide poor color predictions for certain types of layered materials. We therefore propose a simple method based on parameters of the model to check the precision of the two-flux model for a given type of coating

Reflectance of vegetation, soil, and water

The author has identified the following significant results. Bands 4, 5, and 7 and 5, 6, and 7 were best for distinguishing among crop and soil categories in ERTS-1 SCENES 1182-16322 (1-21-73) and 1308-16323 (5-21-73) respectively. Chlorotic sorghum areas 2.8 acres or larger in size were identified on a computer printout of band 5 data. Reflectance of crop residues was more often different from bare soil in band 4 than in bands 5, 6, and 7. Simultaneously acquired aircraft and spacecraft MSS data indicated that spacecraft surveys are as reliable as aircraft surveys. ERTS-1 data were successfully used to estimate acreage of citrus, cotton, and sorghum as well as idle crop land

A Unified model for color prediction of halftoned prints

This study introduces a new model and a new mathematical formulation describing the light scattering and ink spreading phenomena in printing. The new model generalizes the classical Kubelka-Munk theory, and unifies it with the Neugebauer model within a single mathematical framework based on matrices. Results like the Saunderson correction, the Clapper-Yule equation, the Murray-Davis relation and the Williams-Clapper equation are shown to be particular cases of the new model. Using this new theoretical tool, the reflection spectra of 100 samples printed on high quality paper by two different ink-jet printers were computed with an average prediction error of about ΔE = 2.1 in CIELAB

Affordable spectral measurements of translucent materials

We present a spectral measurement approach for the bulk optical properties of translucent materials using only low-cost components. We focus on the translucent inks used in full-color 3D printing, and develop a technique with a high spectral resolution, which is important for accurate color reproduction. We enable this by developing a new acquisition technique for the three unknown material parameters, namely, the absorption and scattering coefficients, and its phase function anisotropy factor, that only requires three point measurements with a spectrometer. In essence, our technique is based on us finding a three-dimensional appearance map, computed using Monte Carlo rendering, that allows the conversion between the three observables and the material parameters. Our measurement setup works without laboratory equipment or expensive optical components. We validate our results on a 3D printed color checker with various ink combinations. Our work paves a path for more accurate appearance modeling and fabrication even for low-budget environments or affordable embedding into other devices

Digital Color Imaging

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

Image segmentation and pigment mapping of cultural heritage based on spectral imaging

The goal of the work reported in this dissertation is to develop methods for image segmentation and pigment mapping of paintings based on spectral imaging. To reach this goal it is necessary to achieve sufficient spectral and colorimetric accuracies of both the spectral imaging system and pigment mapping. The output is a series of spatial distributions of pigments (or pigment maps) composing a painting. With these pigment maps, the change of the color appearance of the painting can be simulated when the optical properties of one or more pigments are altered. These pigment maps will also be beneficial for enriching the historical knowledge of the painting and aiding conservators in determining the best course for retouching damaged areas of the painting when metamerism is a factor. First, a new spectral reconstruction algorithm was developed based on Wyszecki’s hypothesis and the matrix R theory developed by Cohen and Kappauf. The method achieved both high spectral and colorimetric accuracies for a certain combination of illuminant and observer. The method was successfully tested with a practical spectral imaging system that included a traditional color-filter-array camera coupled with two optimized filters, developed in the Munsell Color Science Laboratory. The spectral imaging system was used to image test paintings, and the method was used to retrieve spectral reflectance factors for these paintings. Next, pigment mapping methods were brought forth, and these methods were based on Kubelka-Munk (K-M) turbid media theory that can predict spectral reflectance factor for a specimen from the optical properties of the specimen’s constituent pigments. The K-M theory has achieved practical success for opaque materials by reduction in mathematical complexity and elimination of controlling thickness. The use of the general K-M theory for the translucent samples was extensively studied, including determination of optical properties of pigments as functions of film thickness, and prediction of spectral reflectance factor of a specimen by selecting the right pigment combination. After that, an investigation was carried out to evaluate the impact of opacity and layer configuration of a specimen on pigment mapping. The conclusions were drawn from the comparisons of prediction accuracies of pigment mapping between opaque and translucent assumption, and between single and bi-layer assumptions. Finally, spectral imaging and pigment mapping were applied to three paintings. Large images were first partitioned into several small images, and each small image was segmented into different clusters based on either an unsupervised or supervised classification method. For each cluster, pigment mapping was done pixel-wise with a limited number of pigments, or with a limited number of pixels and then extended to other pixels based on a similarity calculation. For the masterpiece The Starry Night, these pigment maps can provide historical knowledge about the painting, aid conservators for inpainting damaged areas, and digitally rejuvenate the original color appearance of the painting (e.g. when the lead white was not noticeably darkened)