Subtractive Color Mixture Research Articles

Slightly doped hydroxyapatite pigments of subtractive color with high near-infrared reflectance

A novel series of high near-infrared (NIR) reflective Ca5(PO4)3OH based pigments were synthesized by a solid-phase method. Slight single doping of Fe, Mn, and Cu can change white hydroxyapatite into yellow-orange, cyan, and red-violet, respectively. In the apatite-type structure, Fe ions would occupy the site of the Ca2+, Mn ions preferred to form MnO43− in place of PO43−, and Cu ions tended to stay in the hexagonal channel substituting the protons of OH−. When two of the elements were introduced into hydroxyapatite, the color of the co-doped materials followed the principle of subtractive color mixture. Because of the extremely low concentration of dopant, the structure of hydroxyapatite was kept undisturbed, and its high NIR reflectance was also maintained. This paper discussed chromatic properties, spectral analysis, crystalline structure, and morphology of both single-doped and co-doped samples. The economics, environment-friendly, and colorful Ca5(PO4)3OH based material is a potential cool pigment.

New method for observing, demonstrating, and teaching additive color mixture

AbstractThe trichromatic principles of additive and subtractive color mixture have been the foundation of the color reproduction technologies for about 130 years. Yet, today, they remain a poorly understood phenomenon in much of the fine art world as well as the general public. Part of the problem stems from a lack of a simple, effective, widely accessible method for presenting additive color mixtures. This article describes a new, unique means of demonstrating additive color mixture using colored mosaic patterns displayed on computer screens in combination with a simple optical diffuser. Three illustrations composed of primary colored mosaic designs are described along with the underlying theory they are based upon. The potential for this technique as a valuable educational tool for teaching the art and science of color mixture, as well as a new approach for designs in the visual arts, is discussed. Finally, a small representational luminous mosaic image is offered as an example of the creative possibilities in this unexplored realm of art.

Bio-inspired electrochromic skin based on tungsten oxide

Some animals, such as the chameleon, have great capability of camouflage by changing their skin color to avoid detection. This outstanding property have inspired researchers to develop the ability of the materials and devices to mimic chameleon for applications in intelligent wearable and camouflage devices. Tungsten oxide (WO3), switching between blue and transparent, is widely studied due to its large optical modulation but it is difficult to obtain multicolor and flexibility. Here, we design a bio-inspired chameleon skin electrochromic device (ECD) assembled by inorganic electrochromic materials WO3, which can achieve the reversible color changes from yellow, light green to dark green according to subtractive color mixture theory. The flexible ECD exhibits a high optical reflectance modulation of 38.9% at voltage of ± 1.5 V in the wavelength range of 250–2500 nm. Fast response speed of 0.32 s for both coloring and bleaching process is obtained which can be attributed to the porous structure of the WO3 electrochromic layer. The ECD keeps excellent electrochromic performance even under bending conditions, indicating the great flexibility. The inorganic bio-inspired chameleon skin ECD opens new avenues for the design of intelligent and wearable devices.

RGB Colors and Ecological Optics

Object color space is highly structured due to optical constraints (radiant power non-negative, reflectance factors between zero and unity) and ecological context (daylight illuminant). In this setting trichromacy induces a natural geometry through a unique spectral tripartition. Different from null-context colorimetry, one gains two desirable relations: The colorimetric coordinates are coarse-grained spectral reflectance factors and there is a direct link to color experiences, since RGB–coordinates provide ostensive definitions. The framework allows one to deal with subtractive color mixture, source variation, effects of metamerism and relations between scenes and image data in a unified, structured manner. In ecological contexts, colors are effectively object properties. The formal framework is linear algebra and convex geometry. Applications in human biology, computer graphics, design, etc., are immediate.

The Color Top and the Distinction Between Additive and Subtractive Color Mixing [Historical Corner

This article provides a brief overview of the history of the color top as a research instrument. Specific focus is given to James Clerk Maxwell's experiments, which allowed him to obtain the first colorimetric equations using this simple device, and to Hermann von Helmholtz's use of the top to exhibit, in a very simple and clear manner, the difference between additive and subtractive color mixture.

Color e-Paper Technology with Electrochemistry

The demand for global environmental conservation and decrease of CO2 evolution require the development of “new imaging media”, instead of paper. This is called “electronic paper (e-Paper)”. Electrochromism (EC) is defined as a reversible color change by electrochemical reaction and has several features such as color variation, memory property and so on. Electrochromic display (ECD) is therefore a potential candidate to realize full color e-Paper. EC materials showing color changes from clear to the three primary colors such as RGB or CMY should be required to realize full color e-Paper. This paper focuses on novel e-paper technology with electrochemical reaction. First, we will show our recent results on EC materials and devices which show three primary colors (CMY) in subtractive color mixture system1, 2. Electrodeposition is also attractive method to create colors3-5. We will discuss the mechanism of electro-deposition and a wide range of its applications. We also demonstrated novel display device with dual reflective and emissive modes. This is called dual mode display (DMD). DMD enables both reflective and emissive mode of representation which can be chosen as a situation demand. We fabricated DMD by combining both electrochromic (EC) and electrochemiluminescence (ECL) materials in a single cell6, 7. The device functions as an EC cell in the reflective mode, and as an ECL cell in the emissive mode.References; 1) Solar Energy Materials and Solar Cells, 92 136 (2008), 2) Solar Energy Materials and Solar Cells, 104, 140 (2012), 3) Adv. Mater., 24, OP122 (2012), 4) Adv. Mater., 25, 3197 (2013), 5) Chem. Mater, 26, in press (2014). 6) Chem. Lett., 39, 1309 (2010), 7) Phys. Chem. Chem. Phys., 13, 19420 (2011).

34.1: Recent Improvements for Applications of Droplet‐Driven Electrowetting Displays [D3

AbstractFirst applications of a new electrowetting display approach have been developed by adt. This technique is environmental friendly because of its bistability (e.g. replacement of LED indicators), and materials used. Those displays are highly suitable for household applications because they appear white in powerless state. Printer‐like subtractive color mixture and high ambient light contrast ratio pave the way towards electronic billboards.

Theoretical analysis of subtractive color mixture characteristics V—Centroid of subtractive tristimulus values

AbstractIn additive color mixture, when more than two component tristimulus values are given then the mixture result is determined from a linear combination of the components. On the other hand, in subtractive color mixture, the resultant tristimulus values are not uniquely determined from component tristimulus values. Hence, analyses regarding the minimum and the maximum bounds are very important to understand the possible ranges of tristimulus values of subtractive color mixture. In our previous series of articles, several theorems have been proven related to the bounds. In addition to the values, the centroid of a possible range is very important and essential to the prediction of subtractive color mixture. In the present article, several theorems related to the centroid are provided and proven. © 2006 Wiley Periodicals, Inc. Col Res Appl, 31, 418–424, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20247

Theoretical analysis of subtractive color mixture characteristics IV—Theorems on ideal color and tristimulus dimension

AbstractGiving a continuation to our work to understand the characteristics of the tristimulus values in colors obtained by subtractive color mixture, we extend several theorems provided in our previous articles. Previously, we started proving theorems for a single dimension, considering only individual tristimulus values. In the present article, the one‐dimensional discussion is extended to the three‐dimensional discussions of the tristimulus space. These theorems establish the absolute lower and upper bounds for tristimulus values of subtractive color mixtures of the ideal color. The results contribute toward a comprehensive modeling of subtractive color mixture. © 2005 Wiley Periodicals, Inc. Col Res Appl, 30, 427–437, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.

Theoretical analysis of subtractive color mixture characteristics III—Realistic colorants and single tristimulus dimension

AbstractContinuing our work to further understand the characteristics of stimulus values of a single tristimulus dimension in colors obtained by subtractive color mixture, discussions proceed related to realistic colorants. New theorems are intended to provide for the establishment of bounds for realistic colorants in mixtures when stimulus measurements of the constituent single‐colorant samples and the illuminant are obtainable. Related to the new theorems, a formulation is derived for the calculation of the bounds of realistic colorants whose spectral transmittances are represented by weighted combinations of basic functions. By solving the formulation, numerical illustrations are provided for various conditions. The results contribute toward a comprehensive modeling of subtractive color mixture. © 2005 Wiley Periodicals, Inc. Col Res Appl, 30, 354–362, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.

Theoretical analysis of subtractive color mixture characteristics II—General colorants and single tristimulus dimension

AbstractTo further understand the characteristics of the stimulus values in colors obtained via subtractive color mixture, new theorems are provided. The theorems aim to establish bounds on mixtures of colorants given stimulus measurements of the constituent single‐colorant samples and the illuminant. Previously we only proved theorems for the ideal color. In the present article, new theorems related to the removal of the restriction of the ideal color are provided and establish bounds for all cases of spectral transmittances. The results of this article contributes to a systematization of subtractive color mixture. © 2004 Wiley Periodicals, Inc. Col Res Appl, 29, 354–359, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20043

Theoretical analysis of subtractive color mixture characteristics

AbstractUnderstanding the characteristics of the stimulus values of colors obtained by subtractive color mixture is not easy, compared with those obtained by additive color mixture, since the relationship between superimposed absorption media and the stimulus values is not simple. In this article, using the assumption of the Lambert‐Beer model for subtractive color mixture, we prove several theorems regarding the stimulus values of colors obtained by subtractive color mixture. Although these theorems are proved theoretically, numerical illustrations are also shown to confirm the theorems. The results of this paper will contribute to a systematization of subtractive color mixture. © 2003 Wiley Periodicals, Inc. Col Res Appl, 28, 175–181, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.10143

Psychophysical model of chromatic perceptual transparency based on substractive color mixture.

Variants of Metelli's episcotister model, which are based on additive color mixture, have been found to describe the luminance conditions for perceptual transparency very accurately. However, the findings in the chromatic domain are not that clear-cut, since there exist chromatic stimuli that conform to the additive model but do not appear transparent. We present evidence that such failures are of a systematic nature, and we propose an alternative psychophysical model based on subtractive color mixture. Results of a computer simulation revealed that this model approximately describes color changes that occur when a surface is covered by a filter. We present the results of two psychophysical experiments with chromatic stimuli, in which we directly compared the predictions of the additive model and the predictions of the new model. These results show that the color relations leading to the perception of a homogeneous transparent layer conform very closely to the predictions of the new model and deviate systematically from the predictions of the additive model.

Theoretical Analysis of Subtractive Color Mixture Characteristics

Theoretical Analysis of Subtractive Color Mixture Characteristics

Computational theory of color transparency: recovery of spectral properties for overlapping surfaces

A computational theory of color transparency for color images containing X junctions is described. This theory is based on physical models of color transparency under conditions of additive or subtractive color mixture that describe the relationship among four colors at an X junction. Algorithms are derived for recovering transmittance and surface reflectance functions of a transparent medium from a set of sensor responses at an X junction. The algorithms are based on the ability to describe surface reflectance and transmittance functions by using a linear combination of orthogonal basis functions. We also address algorithms for determination of depth ordering of overlapping surfaces and the type of color mixture by checking the physical realizability of recovered functions.

Fast algorithm for computing color gamuts

AbstractA fast and accurate algorithm for computing color gamuts has been developed. In the form presented here for illustration, color gamuts are computed from the dye amounts of subtractive color mixtures. Based on the one‐to‐one correspondence between dye amount space and color space, the simple four‐step algorithm performs a boundary search in dye amount space and a map over to color space. Application to block dyes and commercial reversal film dyes on a desktop computer demonstrates the algorithm's validity, accuracy, applicability, and exceptional speed. © 1993 John Wiley & Sons, Inc.

Perception of transparency in man and machine

The different tactics employed by human and machine vision systems in judging transparency are compared. Instead of luminance or reflectance (relative luminance), the human visual system uses lightness, a nonlinear function of reflectance, to estimate transparency. The representation of intensity information in terms of lightness restricts the operations that can be applied, and does not permit solving the equations describing the occurrence of transparency. Instead, the human visual system uses algorithms based on simple order and magnitude relations. One consequence of the human visual system not using a mathematically correct procedure is the occurrence of nonveridical perceptions of transparency. A second consequence is that the human visual system is not able to make accurate judgments of the degree of transparency. Figural cues are also important in the human perception of transparency. The tendency for the human visual system to see a simple organization leads to the perception of transparency even when the intensity pattern indicates transparency to be physically impossible. In contrast, given the luminances or reflectances, a machine vision system can apply the relevant equations for additive and subtractive color mixture to give veridical and quantitatively correct judgments of transparency.

The perception of transparency with achromatic colors.

Metelli has proposed a model of the intensity relationships in perceptual transparency based on Talbot’s law of color fusion. Four constraints follow from the application of Talbot’s law. Experiments 1 and 2 show that violations of constraints i and ii adversely affect the perception of transparency, while violations of constraints iii and iv do not. Many common occurrences of transparency are in terms of subtractive, rather than additive, color mixture. The constraints derived from the Metelli model are also shown to hold for subtractive color mixture with a filter. An assumption of the Metelli model is that the degree of perceived transparency varies linearly with reflectance. Experiment 3 indicates that the degree of perceived transparency with “partim transparency” varied linearly, not with reflectance, but with lightness, a nonlinear function of reflectance. Experiment 4 indicates that judgments of the degree of transparency with “complete transparency” are based on stimulus relations that differ from those that determine whether the perception of transparency occurs. The results are discussed in terms of how the pattern of intensities relates to other stimulus information, such as figural configuration, in producing the perception of transparency.

Some Misunderstandings about Color Perception, Color Mixture and Color Measurement

Alan Lee's criticisms of Josef Albers' concepts of color [1] give me an opportunity to try to clarify some basic matters concerning color perception, color mixture, color interaction and color measurement. I have long been convinced that a major culprit responsible for the many confusions, misunderstandings, and incorrect statements about color is our use of the language. When we say that something looks blue or yellow, red or green, white or black, light or dark, we are using these color terms to describe what we see. If we have grown up in a normative language system, and if we have normal color vision, then we know what we are talking about when we use color terms in this way. We are categorizing a perceptual experience, and an audience who shares our language and a comparable color vision mechanism understands our statements. On the other hand, when we say that we mix yellow and blue to get green, or alternatively that we mix yellow and blue to get white, our readers or listeners usually do not know what we are talking about in the same way. The reason for this is that we have not said what we are mixing or how we are producing the mixture. We might be placing two pigments on top of each other on a palette and using a palette knife to blend them into a homogeneous mixture before applying this mixture to a canvas or other material substrate. We might be placing two pigments on a canvas next to each other in an array of tiny dots that cannot be resolved as individual dots when we step back from the canvas, but will rather look like a uniform area of some color. The first procedure is subtractive color mixture, and the second, pointillist technique, is an example of spatial color mixture. The mixture results will differ in the two cases, but we will not be able to say what the result is in either case until we know something more about the pigments that are used. More often than not, the names blue and yellow are just that: they are category names or labels that include a wide gamut of appearances. The appearance of the pigment labelled blue, when looked at alone, might be more precisely described as reddish-blue or greenish-blue or a blue that appears to have no trace of either reddish or greenish hue in addition to its blueness. The same is true for the pigment labelled yellow. Consequently, when Josef Albers, who puts practice before theory, and who makes it very clear that trial and error is part of the painter's craft, says that he puts blue and yellow dots in a pointillist array and gets green from their spatial mixture, he is certainly misleading the reader, but he might well be telling the truth. This is because his trial and error procedure would certainly have led him, if he wanted to get green from spatial mixture, to use a yellow pigment that by itself in larger areas appeared greenishyellow and a blue pigment that appeared greenish-blue. If one were to do this, then the spatial mixture would have a greenish hue.

Additive (and Subtractive) Color Mixtures with a Single Slide Projector

Additive (and Subtractive) Color Mixtures with a Single Slide Projector