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Consumer behavior is complicated. In the cosmetic market, personal intuition and fashion trends for color selection are guidelines for consumers. A systematic method for female facial skin-color classification and an application in the makeup market are proposed in this study. In this article, face recognition with a large number of images is first discussed. Then, an innovative method to capture color at selected points is presented and complexion-aggregated analysis is performed. This innovative method is an extension of face-recognition theory. Images in RGB format are converted to CIELAB format during data collection and then Fuzzy C-means theory is used to cluster and group the data. The results are classified and grouped in Lab value and RGB index. Two programs are created. The first program, “FaceRGB,” captures color automatically from images. The second program, “ColorFCM,” clusters and groups the skin-color information. The results can be used to assist an expert system in the selection of customized colors during makeup and new-product development.

The state of chromatic adaptation was investigated by using the two-room technique. This technique involves a subject in a room who looks a white board in a separate test room through a window and judges the color of the window using the elementary color naming method. When the subject room is illuminated with a colored light and the test room with a white light, the window appears to be a very vivid color, for which the apparent hue depends on the color of the subject room. The color is referred to as the adapted color. The subject also evaluated the appearance of the illumination color of the subject room, which is called the adapting color. Two types of illuminating light in the subject room, fluorescent lamps with 7 colors and LED lamps with 19 colors, were employed. The adapting and the adapted colors were plotted on a polar diagram that was used in the opponent color theory, from which the hue angles were obtained. The hue angle difference between the two colors did not appear to be 180° except for one pair of adapting and the adapted colors, which implies that chromatic adaptation does not follow the opponent color concept. An improvement was achieved to explain the results by introducing complementary colors relation between the adapting and adapted color.

A workflow for the color reproduction of digital still images for the purpose of cultural heritage digitization is presented. An analysis was performed to determine the effect of RAW to TIFF transformation; RGB to CIE L*a*b* transformation; white balancing; use of standard color spaces: sRGB, AdobeRGB (1998), ProPhoto RGB, eciRGBv2; custom DCP, and ICC profiles assigning. For the analysis, Color Checker Classic and Digital Color Checker SG targets were used. The precision of the color reproduction was checked against FADGI and Metamorfoze standards. We demonstrate that to obtain high color fidelity reproduction, white balancing and a custom ICC profile are necessary, while DCP profiling could be omitted. © 2016 Wiley Periodicals, Inc. Col Res Appl, 42, 333–336, 2017

A method to reconstruct spectral reflectance from RGB images is presented without priori knowledge of camera's spectral responsivity. To obtain the spectral reflectance of a pixel or region in images, this method assumes that reflectance is a weighted average of reflectances of samples in a selected training group, in which all samples have smaller color difference with that pixel or region. Four proposed weighting modes with different selected numbers of training samples were investigated. Among them, the inverse square weighting mode obtains the best performance, and it is not very sensitive to the selected training samples number. Experimental results show that all weighting modes outperform the traditional method in terms of root mean squared error and Goodness-of-Fit Coefficient between the actual and the reconstructed reflectances as well as color differences under the other light condition. © 2016 Wiley Periodicals, Inc. Col Res Appl, 42, 327–332, 2017

In this article, we present an adaptive color similarity function defined in a modified hue-saturation-intensity color space, which can be used directly as a metric to obtain pixel-wise segmentation of color images among other applications. The color information of every pixel is integrated as a unit by an adaptive similarity function thus avoiding color information scattering. As a direct application we present an efficient interactive, supervised color segmentation method with linear complexity respect to the number of pixels of the input image. The process has three steps: (1) Manual selection of few pixels in a sample of the color to be segmented. (2) Automatic generation of the so called color similarity image (CSI), which is a gray level image with all the gray level tonalities associated with the selected color. (3) Automatic threshold of the CSI to obtain the final segmentation. The proposed technique is direct, simple and computationally inexpensive. The evaluation of the efficiency of the color segmentation method is presented showing good performance in all cases of study. A comparative study is made between the behavior of the proposed method and two comparable segmentation techniques in color images using (1) the Euclidean metric of the a* and b* color channels rejecting L* and (2) a probabilistic approach on a* and b* in the CIE L*a*b* color space. Our testing system can be used either to explore the behavior of a similarity function (or metric) in different color spaces or to explore different metrics (or similarity functions) in the same color space. It was obtained from the results that the color parameters a* and b* are not independent of the luminance parameter L* as one might initially assume in the CIE L*a*b* color space. We show that our solution improves the quality of the proposed color segmentation technique and its quick result is significant with respect to other solutions found in the literature. The method also gives a good performance in low chromaticity, gray level and low contrast images.© 2016 Wiley Periodicals, Inc. Col Res Appl, 00, 000–000, 2016

The description of device color gamut is very important for color gamut mapping, which plays an important role in cross-media color reproduction. To get a more accurate color gamut boundary, several gamut boundary description (GBD) methods have been presented in the past; however, many problems still exist in the current algorithm (e.g., accuracy and speed). In this study, we propose a new device GBD method based on irregular segmentation and evaluate it against other GBD algorithms. In the irregular segmentation method, the device color gamut is divided into the high-chroma and the low-chroma color parts, and the high-chroma parts are divided into more segments through the CIELAB a*b* plane when calculating color gamut descriptors. After that, in each segment, the radii between the color points and the center point are calculated. For the color points located in the high-chroma parts, the color point with the biggest radius is selected as the gamut boundary descriptor, and for that in the low-chroma parts, if the corresponding outer segments are empty, the color point with the biggest radius is selected as the gamut boundary descriptor. Then, the gamut boundary descriptors are visualized in CIELAB color space using triangulation method. Finally, the irregular segmentation method is evaluated in contrast with other GBD methods using gamut mismatch index. The results show that the irregular segmentation method performs better in accuracy and has smaller variance. © 2016 Wiley Periodicals, Inc. Col Res Appl, 2016

The study investigated the optimal display color for comfortable use of smartphones at night under low illuminance, while not distorting the perceived quality of displays. Two phases of psychophysical experiments were conducted to judge perceptibility and acceptability of the displays in various shades of white. The experimental results showed that the scores in acceptability were always higher than those in perceptibility all across the hues, and yellow received the highest scores in acceptability among the six hue categories. This can be interpreted that the observers have the intention of using a display in a yellow shade of white even though it is not perceived as pure white. Through the analysis, a white in yellow shade with the RGB values of 255, 255, and 230 was determined as the optimal display color for nighttime smartphone users regardless of display luminance or contents. The proposed display color supports physiological comfort by reducing the blue light, which involves an adverse effect on the biological system, and provides psychological satisfaction by allowing users to decide the color within the range of the user's acceptable threshold. © 2016 Wiley Periodicals, Inc. Col Res Appl, 42, 60–67, 2017

A new spectral reflectance estimation method based on CIE XYZ values under multi-illuminants was proposed to obtain multi-spectral images accurately by using digital still cameras. CIE XYZ values under multi-illuminants were initially predicted from raw RGB responses by using a polynomial model with local training samples. Then, spectral reflectance was constructed from the predicted CIE XYZ values via the pseudo-inverse method. Experimental results indicated that the new spectral reflectance estimation method significantly outperformed the traditional colorimetric characterization method without requiring extra training samples or greatly increasing computational complexities. © 2016 Wiley Periodicals, Inc. Col Res Appl, 2016

The current Retinex algorithm processes the RGB channels separately for color image enhancement. However, it changes the ratios of RGB components and also causes some serious problems, such as color distor- tion, color noise, and the halo artifacts. To solve these issues, we propose a novel algorithm based on color space fusion. The single scale Retinex with fast mean fil- tering is applied to the luminance component in hue-satu- ration-value (HSV) color space. An enhancement adjustment factor is introduced to avoid color distortion and noise amplification. Then, the surrounding function is replaced by a small scale Gaussian filter in RGB color space to eliminate the halo artifact. A parameter is involved to keep the color natural when the reflection is estimated. Finally, the enhanced color image is con- structed from the weighted averaging results of these two steps. The subjective and objective evaluations of many different backlight images captured by different cameras are implemented to verify the validity of the proposed algorithm in our experiments. The experimental results show that the proposed algorithm can not only signifi- cantly suppress the halo effect and noise amplification, but can also remove color distortion. Our proposed algo- rithm is superior to the multi-scale Retinex with color restoration approach and other state-of-the-art methods. V C 2014 Wiley Periodicals, Inc. Col Res Appl, 00, 000-000, 2014; Pub

To recognize the layout of color yarns of single-system-melange color fabric automatically, a novel FCM-based stepwise classification method is proposed in this article. This method consists of three main steps: (1) warp yarn segmentation, (2) weft color recognition, and (3) the layout of color warps recognition. In the first step, the yarn segmentation method based on mathematical statistics of subimages is adopted to localize warp yarns preliminarily; and then the segmentation results of warp yarn are corrected by misrecognized-boundary remove and missing-boundary interpolation. In the second step, the weft color is extracted based on RGB color histograms of whole fabric image. In the third step, the pixels in each warp yarn are classified into two clusters by fuzzy C-means clustering (FCM) algorithm in CIELAB color model separately, and the preliminary recognized layout of color warps is obtained. All warp colors are clustered by FCM algorithm in CIELAB color model again and the precise layout of color warps is output. The experimental and theoretical analysis proved that the proposed method can recognize the layout of color yarns of single-system- melange color fabrics with satisfactory accuracy and good robustness. © 2015 Wiley Periodicals, Inc. Col Res Appl, 40, 626–636, 2015

Colour remains one of the key factors in presenting an object and consequently has been widely applied in retrieval of images based on their visual contents. However, a colour appearance changes with the change of viewing surroundings, the phenomenon that has not been paid attention yet while performing colour-based image retrieval. To comprehend this effect, in this paper, a chromatic contrast model, CAMcc, is developed for the application of retrieval of colour intensive images, cementing the gap that most of existing colour models lack to fill by taking simultaneous colour contrast into account. Subsequently, the model is applied to the retrieval task on a collection of museum wallpapers of colour-rich images. In comparison with current popular colour models including CIECAM02, HSI, and RGB, with respect to both foreground and background colours, CAMcc appears to outperform the others with retrieved results being closer to query images. In addition, CAMcc focuses more on foreground colours, especially by maintaining the balance between both foreground and background colours, while the rest of existing models take on dominant colours that are perceived the most, usually background tones. Significantly, the contribution of the investigation lies in not only the improvement of the accuracy of colour-based image retrieval, but also the development of colour contrast model that warrants an important place in colour and computer vision theory, leading to deciphering the insight of this age-old topic of chromatic contrast in colour science.

Color is an indispensable indicator of product quality evaluation. To detect the color difference of fabrics, the Levenberg–Marquardt optimized back propagation (BP) algorithm is adopted to extract the color feature values of fabric images. First, RGB values are three inputs of BP neural network, and L*a*b* values measured by spectrophotometer are three outputs of the network. The trained network can obtain the corresponding L*a*b* values conveniently. Then the color difference can be calculated through color difference formula and the characteristic values obtained above. Finally, compared with the color difference calculated by the spectrophotometer, the most appropriate formula can be selected from the four formulas listed in the article (CIEDE2000, CMC, CIE94, and CIELAB) to acquire satisfying results. The experimental results reveal that the color difference of fabrics can be detected with a high accuracy and efficiency with this method. Plenty of duplication workloads and some complex conversion formulas can be avoided, making the acquirement of color difference more efficiently. © 2014 Wiley Periodicals, Inc. Col Res Appl, 40, 311–317, 2015

An integrated spectral imaging system constructed by synchronizing a programmable light source, a high-speed monochrome camera, and a display device is proposed to produce tristimulus images of static and moving objects effectively in real time onto the display. This system is called the CIE-XYZ display. Active spectral illuminants, containing both the device characteristics of camera and display, are projected onto object surfaces as time sequence. The images are captured synchronously by the camera and quickly transmitted to the display device in the RGB signal form so that the accurate tristimulus images are displayed. First, we describe the principle of the CIE-XYZ tristimulus display. The theoretically optimal illuminants contain negative parts in the spectral curves. Second, we design practical illuminants with all positive spectral curves. The color images in our system are composed of the time sequence of RGB component images. Then, the synthesized color images on the display contain color artifacts when objects move fast. An image processing algorithm for correcting the motion color artifact is proposed based on optical flow estimation using a graphics processing unit. The comprehensive performance of the proposed system and algorithms is examined using both static and moving objects. © 2014 Wiley Periodicals, Inc. Col Res Appl, 40, 329–340, 2015

For a digital color camera to represent the colors in the environment accurately, it is necessary to calibrate the camera RGB outputs in terms of a colorimetric space such as the CIEXYZ or sRGB. Assuming that the camera response is a linear function of scene luminance, the main step in the calibration is to determine a transformation matrix M mapping data from linear camera RGB to XYZ. Determining M is usually done by photographing a calibrated target, often a color checker, and then performing a least-squares regression on the difference between the camera's RGB digital counts from each color checker patch and their corresponding true XYZ values. To measure accurately the XYZ coordinates for each patch, either a completely uniform lighting field is required, which can be hard to accomplish, or a measurement of the illuminant irradiance at each patch is needed. In this article, two computational methods are presented for camera color calibration that require only that the relative spectral power distribution of the illumination be constant across the color checker, while its irradiance may vary, and yet resolve for a color correction matrix that remains unaffected by any irradiance variation that may be present. © 2013 Wiley Periodicals, Inc. Col Res Appl, 39, 540–548, 2014

Digital image representation is perceptually uniform if a small perturbation of a component value—such as the digital code value used to represent red, green, blue, or luminance—produces a change in light output at a display that is approximately equally perceptible across the range of that value. Most digital image coding systems—including sRGB (used in desktop graphics), BT.709 (used in high-definition television, HD), Adobe RGB (1998) (used in graphics arts), and DCI P3 RGB (used in digital cinema)—represent colour component (pixel) values in a perceptually uniform manner. However, this behavior is not well documented and is often shrouded in confusion. This article surveys perceptual uniformity in digital imaging and attempts to clarify some widely misunderstood aspects of image coding. © 2013 Wiley Periodicals, Inc. Col Res Appl, 39, 6–15, 2014

In the highly competitive display market, manufacturers continuously develop new technologies to improve the image quality of displays. However, color measurement and visual assessment are time-consuming to production lines. A new method to measure and improve color quality of the displays automatically therefore, is urgently needed to the manufacturers. This article proposes a familiar color correction strategy to optimize the colors of different displays by means of creating an image-based color palette which enables color correction for familiar objects (e.g., facial skin, blue sky, or green grass) in the multidisplay systems. To produce the image-based color palette, the 8-bit RGB value of each pixel in an image is transformed to L*d*n* (lightness/dominant color/nondominant color) color channels, and the dominant-color regions in an image are subsequently extracted from the dominant color (d*) channel. The memory color data of familiar objects can be set in reference monitor in advance to determine the dominant color (d*) channel. Then a series of palette colors are generated around a displayed image. The color palette will be displayed as a target for two-dimensional colorimeter shooting to obtain the measured color data. The familiar color correction model was established based on a first-order polynomial regression to achieve a polynomial fit between the measured color data and the reference color data on the color palette. The proposed method provides a solution to correct familiar colors on a displayed image, and maintains the original color gamut and tone characteristic in the multidisplay systems simultaneously. It is possible to achieve the preferred intent of the displayed images by using the proposed familiar color correction method. © 2012 Wiley Periodicals, Inc. Col Res Appl, 39, 154–168, 2014

With the widespread use of commercialized wide-gamut displays, the demand for wide-gamut image content is increasing. To acquire wide-gamut image content using camera systems, color information should be accurately reconstructed from recorded image signals for a wide range of colors. However, it is difficult to obtain color information accurately, especially for saturated colors, if conventional color cameras are used. Spectrum-based color image reproduction can solve this problem; however, bulky spectral imaging systems are required for this purpose. To acquire spectral images more conveniently, a new spectral imaging scheme has been proposed that uses two types of data: high spatial-resolution red, green, and blue (RGB) images and low spatial-resolution spectral data measured from the same scene. Although this method estimates spectral images with high overall accuracy, the error becomes relatively large when multiple different colors, especially those with high saturation, are arranged in a small region. The main reason for this error is that the spectral data are utilized as low-order spectral statistics of local spectra in this method. To solve this problem, in this study, a nonlinear estimation method based on sparse and redundant dictionaries was used for spectral image estimation—where the dictionary contains a number of spectra—without loss of information from the low spatial-resolution spectral data. The estimated spectra are represented by a mixture of a few spectra included in the dictionary. Therefore, the respective feature of every spectrum is expected to be preserved in the estimation, and the color saturation is also preserved for any region. Experiments performed using the simulated data showed that the dictionary-based estimation can be used to obtain saturated colors accurately, even when multiple colors are arranged in a small region. © 2011 Wiley Periodicals, Inc. Col Res Appl, 2013

I describe complementary colors' physiology and functional roles in color vision, in a three-stage theory (receptor, opponent color, and complementary color stages). 40 specific roles include the complementary structuring of: S and L cones, opponent single cells, cardinal directions, hue cycle structure, hue constancy, trichromatic color mixture, additive/subtractive primaries, two unique hues, color mixture space, uniform hue difference, lightness-, saturation-, and wavelength/hue-discrimination, spectral sensitivity, chromatic adaptation, metamerism, chromatic induction, Helson-Judd effect, colored shadows, color rendering, warm-cool colors, brilliance, color harmony, Aristotle's flight of colors, white-black responsivity, Helmholtz-Kohlrausch effect, rainbows/halos/glories, dichromatism, spectral-sharpening, and trimodality of functions (RGB peaks, CMY troughs whose complementarism adapts functions to illuminant). The 40 specific roles fall into 3 general roles: color mixture, color constancy, and color perception. Complementarism evidently structures much of the visual process. Its physiology is evident in complementarism of cones, and opponent single cells in retina, LGN, and cortex. Genetics show our first cones were S and L, which are complementary in daylight D65, giving a standard white to aid chromatic adaptation. M cone later split from L to oppose the nonspectral (red and purple) hues mixed from S+L. Response curves and wavelength peaks of cones L, S, and (S+L), M, closely resemble, and lead to, those of opponent-color chromatic responses y, b, and r, g, a bimodal system whose summation gives spectral-sharpened trimodal complementarism (RGB peaks, CMY troughs). Spectral sharpening demands a post-receptoral, post-opponent-colors location, hence a third stage. © 2011 Wiley Periodicals, Inc. Col Res Appl, 2011

When dealing with hue-saturation-value (HSV) components, one must be very careful about nonlinearity and singularities of the HSV space, which can amplify considerably the sampling errors of the original components, namely, red-green-blue (RGB) channels. Contradictorily, almost all research in computerized image analysis or processing based on HSV (or other nonlinear color space) neglect to account for such inhomogeneous variability. In this article, we present two approaches for estimating the degree of variability of hue and saturation in the HSV space, intended to assist any color image processing or analysis based on such components. Both approaches end up with new estimators of the hue and saturation standard deviation for a pixel distribution of any color sample. The first approach consists in applying error-propagation analysis on the RGB-to-HSV formulation and the second one is based on heuristic rules inferred from geometrical relations between HSV values of pixel distributions. Experiments show that introduced estimators provide very accurate predictions of true H-S deviations obtained from a broad subset of 183 NCS® color samples. © 2011 Wiley Periodicals, Inc. Col Res Appl, 2011

Recently, Logvinenko introduced a new object-color space defining a complete object-color atlas that is invariant to illumination.1 However, the existing implementation for calculating the new atlas's color descriptors is computationally expensive and does not work for all types of illuminants. A new algorithm is presented here that efficiently calculates the required color descriptors over large data sets and across a wide variety of illuminants. Its Matlab implementation has been made available online. The algorithm is then used to explore some features and possible applications of Logvinenko's color atlas. In particular, it is applied to images to investigate the perceptual correlates of the color descriptors; it is used to predict how images change under a change of scene illumination; and it is used to evaluate how changes in illumination and sensor sensitivities affect the mapping from the Munsell to NCS color atlases. © 2011 Wiley Periodicals, Inc. Col Res Appl, 2011

The purpose of this study was to analyze quantitatively the characteristics and images of costume colors in the traditional plays of Korea, China, and Japan. The study focused on the Korean Masque, Beijing Opera, and Kabuki costume colors based on a selection of 1135 color samples. The collected source data were selected by extracting digital color data by using the Eyedropper Tool of Photoshop 7.0. The RGB color data were transformed to H V/C and the attributes of hue and tone were analyzed. Color images were analyzed with the color image scales of IRI Color Design Institute and Shigenobu Kobayashi to increase the validity of the evaluated images. As a result, the “five element colors (red, yellow, purple–blue (PB), white, and black)” from the theory of “Yin-Yang Wu-Xing” were used in the common stage costume colors of the Korean Masque, Beijing Opera, and Kabuki. Red, a preferred Asian color, was used most frequently in the costumes of these three traditional plays. A comparison of the traditional stage costume colors in the three northeast Asian countries revealed a difference in tones rather than in hues. First, the Korean Masque frequently used white in accordance with the tradition of white-clad people and the cultural view of colors in which natural colors were preferred. Additionally, in the Masque, Koreans used colors based on the theory of Yin-Yang Wu-Xing with high-chroma tones. On the other hand, the Beijing Opera exhibited the gorgeous and strong color images of China, by adopting high-chroma colors in the Five Element Color: R, Y, PB, white, and black. Last, in the Kabuki costumes, a variety of white, black, dull, light, dark, strong, vivid, deep, bright, and grayish tones played an important role in showing various color images. The costume color images of the traditional plays of the three countries revealed that all shared the use of dynamic, springy/casual, and gorgeous images in the strong contrast of five element colors. Regarding the differences, the Korean Masque exhibited natural images in favor of natural colors, whereas the Kabuki displayed modern, decent/formal images by using dull, dark, and grayish colors. The study results suggested that the three countries commonly used five element colors from the theory of Yin-Yang Wu-Xing, but that their color images differed in terms of the tones used and the techniques for color combination. These results reflect that colors in the traditional costumes of the three countries are affected by their cultural codes, thereby representing the characteristics ofcertain peoples and cultural circles. © 2011 Wiley Periodicals, Inc. Col Res Appl, 2011

Light reflected from an object contains a range of information about its physical and chemical properties. Changes in the physical properties of an object can sometimes be evident as barely detectable changes of color. Our earlier study (Proceedings of the 15th Color Imaging Conference, Albuquerque, New Mexico, 2007. p 195–200) proposed a method for designing a spectral filter to enhance visual discrimination. Two filters were designed: one to discriminate skin and vein colors on human arms, and other to discriminate human facial colors in the presence and absence of cosmetics. In this study, the filters with theoretically designed spectral transmittances were implemented as real optical filters. Visual inspection of RGB color images taken with a digital camera through the developed optical filters showed clear enhancement of discrimination of two preselected colors. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2012

The development of wide color gamut (WCG) liquid crystal display (LCD) plays an important role in the high-quality television (TV) field. Nowadays, people want their TV or display devices to have the capability of showing vivid colors while keeping skin colors as natural as they remember. Therefore, it is necessary to develop color-correction technologies for WCG LCD system. A new color-correction method named “natural skin-color mapping algorithm” (NSCMA) for WCG LCD is proposed in this study. It can solve the skin-color contour problem in color-corrected images with simple skin-color detection. Its development is based on the concepts of performing color mapping between source hue colors and target hue colors on each hue page. The polynomial regression is also applied to calculate the color mapping conversion matrices. Two color mapping factors called template-size factor and tone-compression factor are designed in NSCMA. The template-size factor is used to adjust target template sizes adequately. The tone-compression factor is designed to control the degrees of image enhancement. For facial skin-color pictures, the appropriate settings of template-size factor and tone-compression factor will get suitable color image rendering on the WCG LCD. It is demonstrated that the WCG LCD can be corrected to show vivid color pictures and keep facial skin colors as natural as possible when the proposed NSCMA is performed. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2011

Although a number of elaborate color con- stancy algorithms have been proposed, methods such as Grey World and Max-RGB are still widely used because of their low computational costs. The Grey World algo- rithm is based on the grey world assumption: the average reflectance in a scene is achromatic. But this assumption cannot be always satisfied well. Borrowing on some of the strengths and simplicity of the Grey World algorithm, W. Xiong et al. proposed an advanced illumination esti- mation method, named Grey Surface Identification (GSI), which identifies those grey surfaces no matter what the light color is and averages them in RGB space. However, this method is camera-dependent, so it cannot be applied on the images from unknown imaging device. Motivated by the paradigm of the GSI, we present a novel iteration method to identify achromatic surface for illumination estimation. Furthermore, the local Grey Edge method is introduced to optimize the initial condition of the iteration so as to improve the accuracy of the proposed algorithm. The experiment results on different image datasets show that our algorithm is effective and outperforms some cur- rent state-of-the-art color constancy algorithms. � 2010 Wiley Periodicals, Inc. Col Res Appl, 00, 000 - 000, 2010; Published

In digital image reproduction, it is often desira- ble to compute image difference of reproductions and the original images. The traditional CIE color difference for- mula, designed for simple color patches in controlled viewing conditions, is not adequate for computing image difference for spatially complex image stimuli. Zhang and Wandell (Proceedings of the SID Symposium, 1996; p 731-734) introduced the S-CIELAB model to account for complex color stimuli using spatial filtering as a prepro- cessing stage. Building on S-CIELAB, iCAM was designed to serve as both a color appearance model and also an image difference metric for complex color stimuli (IST p 33-38). These image difference models follow a similar image processing path to approximate the behavior of human observers. Generally, image pairs are first converted into device-independent coordinates such as CIE XYZ tristimu- lus values or approximate human cone responses (LMS), and then further transformed into opponent-color chan- nels approximating white-black, red-green, and yellow- blue color perceptions. Once in the opponent space, the images are filtered with approximations of human con- trast sensitivity functions (CSFs) to remove information that is invisible to the human visual system. The images are then transformed back to a color difference space such as CIELAB, and pixel-by-pixel color differences are calculated. The shape and effectiveness of the CSF spatial filters used in this type of modeling is highly dependent on the choice of opponent color space. For image differ- ence calculations, the ideal opponent color space would be both linear and orthogonal such that the linear filter- ing is correct and any spatial processing on one channel does not affect the others. This article presents a review of historical opponent color spaces and an experimental derivation of a new color space and corresponding spatial filters specifically designed for image color difference calculations. !2010 Wiley Periodicals, Inc. Col Res Appl, 35, 387-400, 2010; Published online 7 January 2010 in Wiley

The color image space with one kind of merit color image scales (WIP) is derived using the psychophysical method of magnitude estimation method, usually used in visual assessment of color appearance, which can be used to describe the color image meanings of colors of works of art in parallel with those of people. The results show that a new color image space HRU is developed, and the relativity between this space and the CIEL*a*b* color space is also discussed. And, a good relationship between the HRU color image space and the CIEL*a*b* color space can be found. This may be of great advantage to the new color image space HRU in predicting the color image for single color based on the color space CIEL*a*b*. © 2009 Wiley Periodicals, Inc. Col Res Appl, 34, 452–457, 2009

CIE colorimetry breaks down when lights produced by narrow band RGB-LEDs are matched with broad-band lights. A colour matching experiment was set up and matches in a number of parts of the chromaticity diagram have been made, to determine the magnitude of the discrepancy. Differences between visual and instrumental matches increase as one moves in the chromaticity diagram from yellowish white lights toward greenish and bluish lights. CIE TC 1-36 recently suggested newly defined cone fundamentals: Applying a transformation of these to a space similar to the CIE XYZ space enables a much better prediction of the matches to be made. The difference between the visual match and its instrumental prediction decreases by a factor of two or even more. The use of a cone fundamental based colorimetric system is recommended for LED colorimetry. © 2008 Wiley Periodicals, Inc. Col Res Appl, 33, 108–112, 2008

This article describes two methods for N-dimensional device color gamut representation: one is for gamut surface description, the other for gamut volume description. Both methods combine analytical and geometrical approaches. These methods can be applied to any colorant spaces such as 3-Dimensional RGB or CMY, 4-Dimensional CMYK, 6-Dimensional Hexachrome® (CMYKOG), as well as the 14-Dimensional PANTONE MATCHING SYSTEM®. The N-Dimensional gamut surface description method divides the gamut surface into many subsurfaces with only two-colorant variables. The gamut volume description first divides the whole gamut volume into 3D cubes without overlaps; then an analytical, geometrical, or interpolation method can be applied to each cube. Finally, all subgamuts are united to create the whole gamut. The analytical approach or interpolation technology is applied into these methods to predict unknown colors. The result is highly accurate with an average error less than 0.11 ΔEin CIEDE2000 for CMYK space and less than 0.56 ΔEin CIEDE2000 for higher dimensions. © 2007 Wiley Periodicals, Inc. Col Res Appl, 32, 394–408, 2007

Many spectral-recovery methods using RGB digital cameras assume the underlying smoothness of illuminant and reflectance spectra, and apply low-dimensional linear models. The aim of the present work was to test whether a direct-mapping method could be used instead of a linear-models approach to recover spectral radiances and reflectances from natural scenes with an RGB digital camera and colored filters. In computer simulations, a conventional RGB digital camera with up to three colored filters was used to image scenes drawn from a hyperspectral image database. Three measures were used to evaluate recovery with the direct-mapping method: goodness-of-fit, root-mean-square error, and a color-difference metric. It was found that with two and three filters both spectral radiances and reflectances could be recovered sufficiently accurately for many practical applications. With little increase in computational complexity, an RGB camera and a few colored filters can provide significantly better recovery of natural scenes than an RGB camera alone. (c) 2007 Wiley Periodicals, Inc.

In this study, we tried to consider various color appearance factors and device characterization together by visual experiment to simplify the across-media color appearance reproduction. Two media, CRT display (soft-copy) and NCS color atlas (hard-copy), were used in our study. A total of 506 sample pairs of RGB and HVC, which are the attributes of NCS color chips, were obtained according to psychophysical experiments by matching soft copy and hard copy by a panel of nine observers. In addition, a set of error back-propagation neural networks was used to realize experimental data generalization. In order to get a more perfect generalizing effect, the whole samples were divided into four parts according to different hues and the conversion between HVC and RHVCGHVCBHVC color space was implemented. The current results show that the displays on the CRT and the color chips can match well. In this way, a CRT-dependent reproduction modeling based on neural networks was formed, which has strong practicability and can be applied in many aspects. © 2006 Wiley Periodicals, Inc. Col Res Appl, 31, 218–228, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20209

Were it not for an algorithm patch, the color-appearance model CIECAM02 would sometimes be forced to evaluate fractional powers of negative numbers. The artifact arises because the red and green primaries of the initial CAT02 chromatic adaptation lie outside the positive gamut of the Hunt–Pointer–Estevez (HPE) primaries that subsequently convey the color signal in the model. Relocating the chromaticities of the HPE red and green primaries so as to lie on the CAT02 red–green line alleviates the problem, but adds a bit of X and Y to the revised HPE blue. An (x,y) diagram aids in visualizing the CIECAM02 gamut overlaps, with an extension that accommodates the HPE RGB triangle's enclosure of the point at infinity. © 2006 Wiley Periodicals, Inc. Col Res Appl, 31, 142–145, 2006

Two psychophysical experiments were conducted to analyze the role of color attributes in simple tasks involving color matching and discrimination. In Experiment I observers made color matches using three different adjustment control methods. The results showed that the Lightness, Chroma, Hue (LCH) and the Lightness, redness/greenness, blueness/yellowness ({L, r/g, y/b}) adjustment controls elicited significantly better performance than the display RGB controls in terms of both accuracy and time, but were not significantly different from each other. Expert observers performed significantly better than naive observers in terms of accuracy. Experiment II was a replication and extension of the experiment by Melgosa et al. [Color Res Appl 2000; 25: 356–367] in which observers judged differences and similarities for color attributes in pairs of colored patches. At a 95% confidence level, the results from judging difference were significantly better than those from judging similarity. Hue and Lightness were significantly more identifiable than Chroma, r/g, and y/b. These results indicate that people do not have ready access to the lower level color descriptors such as the common attributes used to define color spaces, and that higher level psychological processing involving cognition and language may be necessary for even apparently simple tasks involving color matching and describing color differences. © 2006 Wiley Periodicals, Inc. Col Res Appl, 31, 445–457, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20257

A preprocessing to CIECAM02 input color for color appearance prediction was proposed. In this study, 8640 color appearance matching pairs (NCS color charts with red, green, yellow, and blue backgrounds in a light booth and their reproductions with gray background on a CRT screen) were obtained by psychophysical experiment using the simultaneous-binocular technique. Because only the lightness of background is included in CIECAM02, a color inducing vector based on opponent-colors theory was introduced to preprocess CIECAM02 inputs, so that CIECAM02 may predict the corresponding color of an input color with chromatic background as well. By data fitting, a color preprocessing formula describing a relationship between the color inducing vector and the NCS chromaticness was conducted. Furthermore, the formula's performance was tested and the results showed that it was good for implementing the color appearance prediction of input colors with different chromatic backgrounds.© 2006 Wiley Periodicals, Inc. Col Res Appl, 32, 40–46, 2007; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20287

This article describes the development of the CIE1931 chromaticity coordinates and color-matching functions starting from the initial experimental data of W. D. Wright and J. Guild. Sufficient information is given to allow the reader to reproduce and verify the results obtained at each stage of the calculations and to analyze critically the procedures used. Unfortunately, some of the information required for the coordinate transformations was never published and the appended tables provide likely versions of that missing data. © 2004 Wiley Periodicals, Inc. Col Res Appl, 29, 267–272, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20020

In CRT monitor characterization accuracy is largely affected by the brightness setting on the monitor. At the optimum brightness level, which adjusts the offsets of RGB channels to nearly zero, CRT monitors have a simple relationship between DAC count and luminance so characterization can be achieved accurately. However, since the optimum brightness levels of CRT monitors are different from one another monitor users, have to make adjustments to the monitor themselves. In this study, a simple device named, brightness optimizer, is fabricated to determine the optimum brightness level objectively. This method uses change of curvature in tone reproduction curves plotted in log-log scale, according to the changes of brightness level. In this article, the configuration of the brightness optimizer and the measurement processes are described. The repeatability and the accuracy in the measurement of the optimum brightness level for three different CRT monitors are also evaluated. © 2003 Wiley Periodicals, Inc. Col Res Appl, 28, 468–472, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.10199

Image sources, such as digital camera captures and photographic negatives, typically have more information than can be reproduced on a photographic print or a video display. The information that is lost during the tone/color rendering process relates to both the extended dynamic range and color gamut of the original scene. In conventional photographic systems, most of this additional information is archived on the photographic negative and can be accessed by adjusting the way the negative is printed. However, most digital imaging systems have traditionally archived only a rendered video RGB image. As a result, it is not possible to make the same sorts of image manipulations that historically have been possible with conventional photographic systems. This suggests that there would be an advantage to storing images using an extended dynamic range/color gamut color encoding. However, because of file compatibility issues, digital imaging systems that store images using color encoding other than a standard video RGB representation (e.g., sRGB) would be significantly disadvantaged in the marketplace. In this article, we describe a solution that has been developed to maintain compatibility with existing file formats and software applications, while simultaneously retaining the extended dynamic range and color gamut information associated with the original scenes. With this approach, the input raw digital camera image or film scan is first transformed to the scene-referred ERIMM RGB color encoding. Next, a rendered sRGB image is formed in the usual way and stored in a conventional image file (e.g., a standard JPEG file). A residual image representing the difference between the original extended dynamic range image and the final rendered image is formed and stored in the image file using proprietary metadata tags. This provides a mechanism for archiving the extended dynamic range/color gamut information, which is normally discarded during the rendering process, without sacrificing interoperability. Appropriately enabled applications can decode the residual image metadata and use it to reconstruct the ERIMM RGB image, whereas applications that are not aware of the metadata will ignore it and only have access to the sRGB image. The residual image is formed such that it will have negligible pixel values for those portions of the image that lie within the sRGB gamut, and will therefore be highly compressible. Tests on a population of 950 real customer images have demonstrated that the extended dynamic range scene information can be stored with an average file size overhead of about 8% compared to the sRGB images alone. © 2003 Wiley Periodicals, Inc. Col Res Appl, 28, 251–266, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.10160

In this work, we determine the numerical data of the experimental color-matching functions (cmf's) of three real observers (JAM, MM, and CF) for two small fields (2°). In previous works, these cmf's have been shown generically and expressed only in a new system of unreal X′Y′Z′ primaries. Here, we show results found with these cmf's for the visible spectrum in intervals of 10 nm, from 400 to 700 nm. The data refer to both the RGB CIE-1931 system and a new system of unreal primaries X′Y′Z′, established by a procedure similar to that of the XYZ CIE-1931 system. This transformation was needed, because negative values appeared in various cmf's when they were referred to the XYZ CIE-1931 system. Recently, we have called this new system G94 (Granada ‘94). Here, we also describe the method and calculation of the matrix that enables this transformation; in testing six real observers with new cmf’s, we found positive results. We have used these new and experimental cmf's in several preceding works, as have other authors as well, to whom J. A. Martinez privately communicated the corresponding numerical data. The use of these cmf's by all the authors has led to noteworthy results. © 2003 Wiley Periodicals, Inc. Col Res Appl, 28, 89–95, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.10127

A simple algorithm (amenable to spreadsheets) is described for plotting a luminance contour map of the color gamut of an additive-primary display given the chromaticities of its primaries and screen white. Each contour of the plot represents (in either r,g or x,y coordinates) the polygon of intersection of the RGB cube with a plane of constant Y. Each vertex on a contour is an intersection of 1 of the 12 edges of the RGB cube with the constant-Y plane. Feasibility of an edge as a vertex of the polygon is tested through comparison of the computed r,g coordinates with functions of the luminosity coefficients of the primaries. By ordering the RGB-cube edges in a particular way prior to scanning them for feasibility, one is guaranteed to retrieve the vertices of any constant-Y polygon in convex order. This fact facilitates plotting of the polygons.

Novice designers of visualizations need support to find easy-to-use color schemes for visualizations. This article introduces a method of conspicuity inference for a color selection support system that is applicable to a wide variety of visualizations. In previous research, data on color conspicuity by computer GUI interface were collected by having subjects adjust the relative sizes of two figures on a ground in order to find conspicuity balance. This article outlines a new conspicuity inference system, which uses a neural network to produce a color conspicuity value from the system RGB values of two figures and a potential ground. The output value is the ideal relative area of the two figures. This value is applied to visualization designs by weighting each conspicuity value with a ground coefficient, the relative size of every color in a design. Color selection and evaluation experiments show a significant relationship of conspicuity balance, as inferred by this system, for subjective ease-of-use evaluation scores for 200 novice designs. Topics for future research include developing the system's characteristically simple parameters within the limited scope and integrating conspicuity balance with other factors such as visibility, discriminability, and color harmony. © 2002 Wiley Periodicals, Inc. Col Res Appl, 27, 74–82, 2002; DOI 10.1002/col.10033

During the past years, several papers have been published that question the use of the CIE colour-matching functions in the case of metameric samples. Visually matching samples produced on CRT (Cathode Ray Tube) monitors are metameric to most colour stimuli created by illuminating reflecting materials. As CRT monitors are often used in colour design applications, it seemed important to check how well CIE colorimetry will predict such colour matches. To investigate this problem, we set up an experiment in which painted samples were matched with samples produced on a CRT monitor. The colour of incandescent lamp irradiated Munsell samples were visually matched to the mixture of the RGB primaries of a CRT monitor. Both the reflected colour stimuli of the Munsell samples and the emitted stimuli of the monitor were measured spectroradiometrically. Our results imply that there is an observer-dependent variability among the matches, but we could not find a major difference between the tristimulus data of the hard copy and soft copy presentations that would indicate errors in the CIE colour-matching functions. The measurement accuracy, quantization errors of the monitor, and the achieved accuracy of the colour matches are treated in this study. © 2001 John Wiley & Sons, Inc. Col Res Appl, 26, 436–441, 2001

The digital camera is a powerful tool to capture images for use in image processing and colour communication. However, the RGB signals generated by a digital camera are device-dependent, i.e., different digital cameras produce different RGB responses for the same scene. Furthermore, they are not colorimetric, i.e., the output RGB signals do not directly correspond to the device-independent tristimulus values based on the CIE standard colorimetric observer. One approach for deriving a colorimetric mapping between camera RGB signals and CIE tristimulus values uses polynomial modeling and is described here. The least squares fitting technique was used to derive the coefficients of 3 × n polynomial transfer matrices, yielding a modeling accuracy typically averaging 1 ΔE units in CMC(1:1) when a 3 × 11 matrix is used. Experiments were carried out to investigate the repeatability of the digitizing system, characterization performance when different polynomials were used, modeling accuracy when 8-bit and 12-bit RGB data were used for characterization, and the number of reference samples needed to achieve a reasonable degree of modeling accuracy. Choice of characterization target and media and their effect on metamerism have been examined. It is demonstrated that a model is dependent upon both media and colorant, and applying a model to other media/colorants can lead to serious eye–camera metamerism problems. © 2001 John Wiley & Sons, Inc. Col Res Appl, 26, 76–84, 2001

The nonlinear relationship between luminance and DAC count could be characterized with the simplified model, if optimum brightness level is set. In this study, we propose a technique to set the optimum level of brightness, in which offsets for RGB channels can be assumed to zero, and determine the gamma coefficients from log–log data without nonlinear optimization. The optimum brightness level could be found by measuring a few tones of neutral for the combination of 3 levels of brightness and 2 levels of contrast. This technique has two advantages. It does not require measurements for 0 DAC count, and does not require nonlinear optimization in finding the gamma coefficient of the display system. Two CRT monitors by different manufacturers have been tested. As the result, all monitors could be set to their optimum state with a different combination of brightness and contrast. In that state, the gamma coefficient for each channel could be determined from two measuring data and the tone reproduction characteristics of the RGB channel could be characterized with the simplified equation, neglecting offset and gain. The accuracy of characterization was better than 0.5 ΔE*ab for 125 colors for a monitor having good channel independence. © 2000 John Wiley & Sons, Inc. Col Res Appl, 25, 408–415, 2000

A World Wide Web (WWW) based tool for the learning of color models is presented, along with a methodology of use. The system was developed in Java, allowing its remote use and a high degree of interaction with the user. It shows two color systems (RGB and HSB), users choose their position relative to the solids that define the system and, positioning control points, define the section of the solid to be designed. Both the system and the methodology are desktop-oriented, and are low-to-moderately demanding in terms of both hardware and software. © 2000 John Wiley & Sons, Inc. Col Res Appl, 25, 435–441, 2000

In the present experimental study, we quantify the influence of the brightness and contrast levels of a CRT- color monitor in the color reproduction of 60 Munsell chips distributed throughout the chromatic diagram. The images were captured by two CCD cameras, and the color differ- ences were evaluated after reproducing the chips on a color monitor (the experiment was performed with 3 different monitors) for 9 combinations of brightness-contrast levels. We evaluated the color differences with 3 different formu- las: CIELAB, CIELUV, and CIE94. The results indicate that the optimal settings of a monitor, to minimize the color differences, is a medium or minimum brightness level in combination with a maximum contrast level. This combina- tion ensures a more faithful color reproduction with respect to the original image.© 1999 John Wiley & Sons, Inc. Col Res Appl

In order to produce desired colors on CRT screens, much work has been done on the problem of the CRT colorimetric prediction. However, it would take great pains to overcome the troubles such as the constant channel chromaticity, the gun or channel independence, and the screen background effect, etc., with the conventional prediction methods such as PLCC and PLVC models, etc. To solve such problems, we propose a completely different CRT colorimetric prediction model by using a set of Artificial Neural Networks (ANN), where a set of back-propagation (BP) neural networks is used to perform a nonlinear conversion between RGB values and XYZ values. By comparing some typical conventional CRT colorimetric prediction models with our neural-networks-based model theoretically, the article indicates that our new model can overcome the troubles faced by the conventional models, and by experiment the article shows that our new model can yield a satisfactory prediction result. © 1999 John Wiley & Sons, Inc. Col Res Appl, 24, 45–51, 1999

A colorimetrically characterized computer-controlled CRT display was used to determine closest perceptual color matches of 25 colors when an exact match was not allowed. An artificial but realistic color gamut was created by intersecting the display gamut with a gamut of a Xerox 4920 color laser printer. Each of 21 observers performed color matches between out-of-gamut colors and those on the artificial gamut's edge. Each observer made color matches on 4 different images. The images represented some of the categories that business graphic images can fall into. Between the different image types, there were no multidimensional (MANOVA) statistically significant differences at the 10% confidence level in any of the 25 colors tested. The mapping vectors showed that (1) observers don't make simple matches as assumed by most gamut-mapping experiments done to date, (2) the influence of image content for simple graphical images tested does not have a large effect when the task is to make closest perceptual color matches, and (3) CIELAB hue angle is not uniform enough, especially in blue and cyan regions, to make adequate gamut-mapping transforms. A simple model for clipping type gamut mapping is proposed. Results are compared to predictions of a new gamut-mapping technique that minimizes weighted color difference between the target color and the gamut boundary. © 1997 John Wiley & Sons, Inc. Col Res Appl, 22, 402–413, 1997