Color Theory and Color Management (2)

Perform color management and establish color standards

To produce color, a set of standards must be established for the representation and transmission of colors. Current popular color management systems such as LinoColor, Agfa's Phototone, etc. are all moving in this direction. Through a set of standard specifications (ICC mapping files) describing the color gamut of devices, color computing software is used to perform uniform color gamut conversion. Operation to reduce the color deviation and distortion caused by different color gamuts and specifications during the transmission of color data. To implement these color management systems, we must first find out the color gamut of the device. The most commonly used method to describe the color gamut is CIELab, a set of descriptive color data that converts the wavelength of light into luminance and hue according to the characteristics of the human eye, where L is the brightness of the description color and a represents the color deviation The degree of red greenness, b represents the extent of the color yellow to blue. In the CIELab color space, each person's eye-visible color has a position that belongs to that color. By comparing the distance between the two color positions, we can determine the approximate degree of color on both sides. Since the visible light spectrum is the basis of this set of data, it can cover the colors produced by screens and prints, as well as the color gamut of the eyes of delegations.

For example, to describe the color gamut of a printer, first print some test strips from the printer. These strips include various main colors and colors that are more difficult to reproduce. Then use the spectrometer to measure the CIELab data on the strips, and then use software to convert the data. Written as a comparison file in the ICC format. In addition to the gamut data of the device, the comparison file can also include the production characteristics of the device, such as the black version feature, dot gain value, and so on. With the contrast of the device, the color calculation software can refer to the characteristics of the two devices, and compare the color gamut of the device within the CIELab color space to obtain a better simulation effect. This technology has now reached the stage of production and application, of which the most widely used, is to print the color gamut by screen simulation, and to simulate the printing color gamut by a printer. Since the color gamut of the screen is larger than the color gamut of the print, simulation in this case is also called gamut compression simulation. The entire simulation process is based on the data in the reference file as the basis for calculation, so the generation and management of the reference file becomes the most important task.

The assumption of the color management system

Has a color management system been implemented to achieve the desired effect of color production? To answer this question, you must understand the assumptions behind the color management system. The main task of the color management system is to simulate the data of another known color gamut on the CIELab space based on a known color gamut data. Therefore, it is necessary to assume that two gamuts remain while recording gamut data. status. That is to say, the production status of the equipment-contrast file and the production status when calculating the color gamut must be the same. If the contrast file established yesterday cannot be compared with today's equipment and the production status keeps floating, the color management system cannot play the role of reducing the deviation. An unstable production process may even cause the color management system to expand the color deviation. Therefore, the color management system is more suitable for the design, color separation, proofing and printing at the same time, because it is easier to control the variables in the production process in the same factory.

Color is not only the design element, but also the standard of production receipt. Even if the customer barely accepts a printed product with unsatisfactory color, it may no longer patronize the next time. Many companies lose important customers because of color quality problems. It can be seen that mastering the laws of color presentation and controlling color quality are the technologies that must be mastered in production and production. With advanced equipment alone and without good technical cooperation, in the fierce competition in the industry, it will inevitably be eliminated.

Color detection technology and application of color management
Color has a very important position in the history of human civilization. How to correctly and appropriately apply colors and express colors is one of the most important topics. It is also a common goal pursued by humans. In the present and future scientific and technological civilization also has its importance. For example, today's information and communication technologies are constantly improving, with each passing day, and the transmission and expression of color are more perfect and true color reproduction, that is, WYSI-WYG (What You See Is What You Get'). To achieve this goal, we must have an ideal color vision pattern that is fully consistent with human perception. This ideal color vision mode contains the correct color-difference formula and the chromatic-adaptation model, and the ideal color appearance pattern (Colour-appearance). Model) etc. This ideal color vision mode is the basis for qualitative and quantitative applications of various colors.

Human efforts in color science and technology have made great achievements. For example, the British Commission on Illumination (CIE) has issued human eye color function (2° and 10°), CIExyY color system, CIEL*U*V*, and CIEL*a*b* uniform color space since 1931. And so on, and become a very important content and result of CIE colorimetry. CIE colorimetry has also become the basis for the development of color science research in the world today. In addition, there have been great contributions and achievements in color detection, computer color matching, computer color separation and color transmission technologies. However, in the research and development process of pursuing the goal of the ideal color vision mode, there are still many research and improvement improvements in the application of color detection technology. For example, the color difference formula is used to predict the derivation of large color differences, the evaluation of meta-merism, and the derivation of the color constancy model. In particular, color variability and color constancy are often irritating to both industrial applications and the color of life and art. It can be seen that color variability and color constancy have an absolute impact on the effectiveness of color detection technology. Therefore, the development and achievements of the qualitative and quantitative detection technologies of these two color characteristics are the focus of this report.

Color variation can also be referred to as metamerism, conditional color, or conditional color, and can also be simply defined as: a two-color stimulus has the same color appearance under a reference light source (generally referred to as simulated average sunlight, D65) (ie, The so-called color), but under a certain second light source (such as tungsten light, A) both show a different color appearance (the so-called non-color). This phenomenon is called color variation, and this two-color stimulus is called a metamer. In terms of application, color variations often cause great problems for color-related industries (such as printing, textiles, inks, plastics, color TVs, lighting, architecture, art, etc.) Receive and compensate for serious losses that increase production costs. Therefore, the evaluation of color variability is an important part of color detection technology.

In terms of color variability color detection technology, it can be divided into qualitative method and quantitative method. The commonly used qualitative method is (1) visual inspection method: by using multi-light source standard color lamps, the color or color difference of a color sample pair is observed under different standard light sources. (2) Reflectance curve method: According to the number of intersection points of the object's color reflectivity curve (for transparent objects according to its transmittance curve) to determine the color variability, the more the intersection points, the smaller the color variability. However, there are at least three intersection points, that is, the larger the color variability of the color change, the more the intersection point of the reflectivity curve will be concentrated on the three intersection points. The three intersections are 450 nm, 540 nm, and 610 nm, also known as Barocentric wavelengths. For quantitative methods, CIEL*a*b* is used for object color (CIEL*u*v* for color light source), CMC(ι:c), CIE94, and BFD(ι:c). The formula calculates the color difference of a color sample under different light sources to evaluate the color variability of the color sample pair. In addition, for lighting, a CIE colour rendering index can be used to assess the color rendering of an illumination or artificial light source. In this article, we focus on object colors and discuss the pros and cons of various color variability detection methods and usability.

Color constancy can also be called homochromatic or color constancy. The relative property is the colour non-constancy, which is the heterochromatic co-spectrum. Both color constancy and color variability are two sides of one body, and it is easy to be confused. The simple distinction method is: color constant is for a single color stimulus, and color variability is a two-color stimulus. In other words, if a certain color stimulus has the same color appearance under a certain reference light source and under other light sources, the color stimulus is said to have a color constancy. In everyday life, everyone with a normal color vision will have the same experience, that is, most natural objects have a constant color appearance in different natural light. This phenomenon is color constant. However, due to the advancement of human scientific and technological civilizations, artificial colors or inks and light sources or lighting are changing with each passing day, increasing continuously and in a variety of types, which greatly increases the non-constantness of object colors in daily life and the surrounding environment. Therefore, how to effectively manage color applications has become a very important topic today.

The detection technology of color constancy is to predict the color appearance of any color stimulus under different light sources or lighting or even different media by using the chromatic adaptation model to evaluate its color constancy. In the application, the color adaptation mode can be used to predict the color variability of the color stimuli generated when the ink or dyestuff is used alone or in combination, thereby making the color quality of the product stable or easy to control and manage. At present, the published colorimetric adaptation models are von Kries, Bartl-eson, BFD, CIE (Nay-atani et al.), Hunt, CIEL*a*b*, RLAB, and the forthcoming models LLAB, KL95, Kuo96 et al.