Dictionary‐based estimation of spectra for wide‐gamut color imaging

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     

Categorical color constancy under RGB‐LED light sources

The light‐emitting diode (LED)‐based light sources have been widely applied across numerous industries and in everyday practical uses. Recently, the LED‐based light source consisting of red, green and blue LEDs with narrow spectral bands (RGB‐LED) has been a more preferred illumination source than the common white phosphor LED and other traditional broadband light sources because the RGB‐LED can create many types of illumination color. The color rendering index of the RGB‐LED, however, is considerably lower compared to the traditional broadband light sources and the multi‐band LED light source (MB‐LED), which is composed of several LEDs and can accurately simulate daylight illuminants. Considering 3 relatively narrow spectral bands of the RGB‐LED light source, the color constancy, which is referred to as the ability of the human visual system to attenuate influences of illumination color change and hold the perception of a surface color constant, may be worse under the RGB‐LED light source than under the traditional broadband light sources or under the MB‐LED. In this study, we investigated categorical color constancy using a color naming method with real Munsell color chips under illumination changes from neutral to red, green, blue, and yellow illuminations. The neutral and 4 chromatic illuminants were produced by the RGB‐LED light source. A modified use of the color constancy index, which describes a centroid shift of each color category, was introduced to evaluate the color constancy performance. The results revealed that categorical color constancy under the 4 chromatic illuminants held relatively well, except for the red, brown, orange, and yellow color categories under the blue illumination and the orange color category under the yellow illumination. Furthermore, the categorical color constancy under red and green illuminations was better than the categorical color constancy under blue and yellow illuminations. The results indicate that a color constancy mechanism in the visual system functions in color categories when the illuminant emits an insufficient spectrum to render the colors of reflecting surfaces accurately. However, it is not recommended to use the RGB‐LED light source to produce blue and yellow illuminations because of the poor color constancy.     

Complementary colors theory of color vision: Physiology,color mixture,color constancy and color perception

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     

Color constancy from invariant wavelength ratios. III: Chromatic adaptation theory,model and tests

A theory of chromatic adaptation is derived from Parts I and II, and presented in terms of relative wavelength, purity, and radiant power, leading directly to a predictive model of corresponding hue, chroma, and lightness. Considering that even simple animals have effective color vision and color constancy, the aim was to develop a simple model of complete adaptation. The model is tested against well‐known data sets for corresponding colors in illuminants D65, D50, and A, and for small and large visual fields, and performs comparably to CIECAM02. Constant hue is predicted from Part I's mechanism of color constancy from invariant wavelength ratios, where constant hues shift wavelength linearly with reciprocal illuminant color temperature. Constant chroma is predicted from constant colorimetric purity. Constant lightness is predicted from chromatic adaptation of spectral sensitivity represented by power ratios of complementary colors (rather than cone responses which lack spectral sharpening). This model is the first of its type and is not formatted for ease of computation. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2010     

Optical implementation of spectral filtering for the enhancement of skin color discrimination

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     

Color breakup visibility thresholds for 2‐field sequential colors

Nowadays local primary desaturation has been proved to be an effective method to suppress the color breakup for field‐sequential‐color (FSC) displays. However, little attention has been focused on the interaction between various subfield colors and the color breakup visibility. In this article, a perception experiment was conducted with the help of a 120 Hz 2‐field FSC display to investigate the thresholds of color breakup visibility along different hue directions with a constant white point in the standard color space. The experimental results show that the color breakup visibility is various when using different subfield colors for temporal combination. A relative high threshold value or low sensitivity of color breakup visibility can be observed when subfield colors are chosen along the blue‐yellow direction while becoming perceptible easily along magenta‐cyan direction. The results and analysis of our experiments are promising to optimize the performance of local primary desaturation. Meanwhile, other applications using the temporal color fusion such as tunable lighting can also benefit from the conclusion of our work to suppress the color breakup effect.     

Skin‐color correction method based on hue template mapping for wide color gamut liquid crystal display devices

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     

Applying image‐based color palette for achieving high image quality of displays

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     

Michromatic scope for enhancement of color difference

A michromatic (microscope plus chromatic) scope is a device that enhances the color discrimination between two spectral color datasets. Three spectral filters are required, instead of the conventional red, green, and blue filters, for the implementation of a michromatic camera. In this study, we describe two approaches to the design of these filters: in the first case, the design is based on the direct optimization of the filter characteristics (transmittance), whereas in the second case, the design is based on the nonnegative tensor factorization (NTF) of the spectral datasets. A michromatic camera can be implemented using these filters along with compatible postprocessing in‐camera firmware. Here, we performed experiments with two color datasets: one comprising skin and vein colors, and one comprising skin and cosmetics colors. These were further divided into a training set and a test set. The filters were defined using the training set, and the operation of the filters was tested and magnified using the test set. Our experiments demonstrated that the proposed approaches are suitable for color discrimination. For the first color dataset, the enhancement produced using the optimized filters was up to 252% of the original value, and the average color difference ΔE was increased from 2.82 to 9.93. NTF and preprocessing further enhanced the ΔE up to 21.84. For the second color dataset, NTF and postprocessing enhanced the ΔE from 4.33 to 29.19. The proposed discrimination enhancement could be physically implemented in a designated digital charge‐coupled device camera with proper filter installation and compatible postprocessing. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2010     

Chromatic adaptation transform by spectral reconstruction

A color appearance model (CAM) is an advanced colorimetric tool used to predict color appearance under a wide variety of viewing conditions. A chromatic adaptation transform (CAT) is an integral part of a CAM. Its role is to predict “corresponding colors,” that is, a pair of colors that have the same color appearance when viewed under different illuminants, after partial or full adaptation to each illuminant. Modern CATs can sometimes generate colors with negative tristimulus values. For some imaging applications, it is important to maintain positive tristimulus values when applying a CAT. This article proposes a new CAT that does not operate on the standard von Kries model of adaptation. Instead, it uses a spectral reconstruction technique as an intermediate stage in the process, while still requiring only tristimulus values as inputs. It is demonstrated that the proposed CAT will not generate colors outside the spectral locus or colors with negative tristimulus values. The proposed CAT does not use established empirical corresponding‐colors data sets to optimize performance, as most modern CATs do, yet it performs as well as or better than the most recent CATs when tested against the data sets of corresponding colors.     

Practical method for measuring printed colors on FWA‐treated paper

The virtual fluorescent standard (VFS) method is a new approximation method for the practical measurement of the colorimetric properties of an object treated with fluorescent whitening agent (FWA). The essential requirement of the VFS method is that the bi‐spectral characteristics of the VFS must be similar in curve shape to those of the object to be measured. In the case of an object printed on an FWA‐treated substrate, the bi‐spectral characteristics will vary depending on not only the substrate but also the printed ink films. In this study, two simplified VFS methods, one using the bi‐spectral characteristics of the substrate and the other using those of typical paper as the VFS instead of those similar to each object, were evaluated. The evaluation was performed using two instrument models for the VFS method with the different illuminations with five sets of 13 samples printed in different colors by five different printer/paper combinations. In this evaluation, the total spectral radiance factor of each sample was obtained by simulated measurement, that is, it was calculated based on the bi‐spectral radiance factor of the sample and the spectral power distributions of the light source of the instrument. The total spectral radiance factor of each sample under D50 obtained using both VFS models and CIE L*a*b* values derived therefrom were compared with those by the reference model with ideal D50 illumination. Although the samples are limited, the results shows that both simplified VFS methods remarkably reduce the errors due to fluorescence when compared to the conventional method. © 2011 Wiley Periodicals, Inc. Col Res Appl, 2012     

Semantic interpretation of color differences and color‐rendering indices

A series of visual experiments were carried out to rate the similarity of color appearance of two color stimuli on categorical and continuous semantic rating scales. Pairs of color stimuli included two copies of the same colored real or artificial object illuminated by a test light source and a reference light source. A formula was developed to predict a category of color similarity (e.g., “moderate” or “good”) from an instrumentally measured color difference. Given a numeric value of a color difference between the two members of a pair of colors, for example, 2.07, the formula is able to predict a category of color similarity, for example, “good.” Because color‐rendering indices are based on color differences, the formula could be applied to interpret the values of the new color‐rendering index (n‐CRI or CRI2012) in terms of such semantic categories. This semantic interpretation enables nonexpert users of light sources to understand the color‐rendering properties of light sources and the differences on the numeric scale of the color‐rendering index in terms of regular language. For example, a numeric value of 87 can be interpreted as “good.” © 2013 Wiley Periodicals, Inc. Col Res Appl, 39, 252–262, 2014; Published online 14 March 2013 in Wiley Online Library ( wileyonlinelibrary.com ). DOI 10.1002/col.21798     

Exact location of consensus and consistency colors in the osa‐ucs for the italian language

In a previous work, the authors reported on the results of a color naming experiment performed on native Italian speakers regarding the location of focal colors and centroids in the Uniform Color Scales of the Optical Society of America color system. That work was aiming at comparing such data with those previously obtained by Boynton and Olson (B&O) accounting for the differences in the paradigm and the language. The number of consistency and consensus colors in the different lightness plans was also reported but no information was provided on their placement. Though, such information is very important for any subsequent modeling stage. The objective of this article is to fill such a gap and share such data with the scientific community to provide a reference database for future investigation. Three different datasets were considered: the extended OSA (E‐OSA), the reduced OSA (R‐OSA), and the B&O's (B&O) sets of reference colors. Results show a good overlap among the locations of the consensus colors in the {L, j, g} color model between B&O and the subset of E‐OSA colors overlapping with the B&O 424 colors (R‐OSA), as well as a strong agreement on consistency. Furthermore, a close proximity among the centroids of homologue regions for the majority of the classes was found. © 2012 Wiley Periodicals, Inc. Col Res Appl, 38, 437–447, 2013     

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

To 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     

An intelligent skin‐color capture method based on fuzzy C‐means with applications

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.     

Color‐emotion associations,designing color schemes for urban environment‐architectural settings

Color in urban design has become an important issue, each city may present different colors which help to define and describe its architectural features. In the study, color in urban design with architectural setting is studied, façade colors are analyzed with a specific emphasis on the following research questions; “Can color schemes be designed in respect to color‐emotion associations? ” and “Are color‐emotion associations affective while designing architectural setting‐urban environment?.” Non‐color experts, 170 people, from different European and non‐European countries were asked to match the most appropriate adjectives with the given street views in accordance to their color schemes. In the first step, the effect of color is identified in relation to architectural environment‐urban setting, second the relative effect of color is studied as a component of the material. A categorical specification on color cognition and linguistic level of representation is attempted. The results can be a starting point to highlight the importance of preparing color schemes in regard to color‐emotion associations. Abstract color schemes may also provide us an idea about image setting, especially at design process stage. In the study, keywords are linked as environment‐response pairs; such as quiet, calming, lively, exclusive, reserved, and natural. Human psychophysical structure such as “warm‐cool,” “heavy‐light” in regard to visualizing certain colors are evaluated and described in terms of building materials.     

Color constancy,color‐mixing ability,and color inference

In the laboratory, the performance of color constancy has always been unstable. The variables posed by the subjects themselves tend to be neglected. In this study, a simple color‐mixing test was used to sort subjects into three groups. They were also provided with hue and brightness in a fixed color order as guidance during experimental tasks in an attempt to observe any changes in cognitive skills among subjects of varying color‐mixing abilities under changed illuminations. Three hypotheses were proposed: (1) Matching hypothesis: people remember and apply the spatial locations of color surrounds to the target color to achieve color constancy; (2) Comparing hypothesis: people identify the relative difference between color surrounds to achieve color constancy; and (3) Reasoning hypothesis: people compare the color surrounds and refer to color knowledge accumulated in the past to achieve color constancy through reasoning. The experimental results were as follows if the Comparing hypothesis is taken into account, (a) when hue guidance is hidden the subjects' identification rate (IR) performance supported the Reasoning hypothesis; (b) when hue guidance was shown, the IR performance of subjects in all three groups supported the Matching hypothesis. Based on these results, this study offers two recommendations: (a) color surrounds with a fixed relative location should be avoided because spatial location memory leading to people using matching skills and (b) subjects should be screened based on their color‐mixing ability because significant differences in color constancy performance exist between people with varying levels of color‐mixing ability. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2010     

Color separation for colored fiber blends based on the fuzzy C‐means cluster

Colored fibers can be blended in a certain proportion to achieve a specific color. It is a very hard task for the colorist to find a good recipe to meet the final product without the aid of computer. In this article, a color separation method for the colored fiber blends is discussed to substitute for some manual work. The fuzzy C‐means cluster is a way to group the color in the colored fiber blends image. The distance index, which is a key factor during the fuzzy C‐means cluster process, is calculated in the RGB color space and the HSV color space with some transformation. The final experiment result proved that the colors of each pixel in the blends' image can be replaced by corresponding cluster center associating colors in the HSV color space, and the main texture as well as the main color information about the fibers in the image is preserved. © 2011 Wiley Periodicals, Inc. Col Res Appl, 2012     

Automatic detection of layout of color yarns of yarn‐dyed fabric. Part 1: Single‐system‐mélange color fabrics

To recognize the layout of color yarns of single‐system‐mélange 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‐ mélange color fabrics with satisfactory accuracy and good robustness. © 2015 Wiley Periodicals, Inc. Col Res Appl, 40, 626–636, 2015     

Colour‐imager characterization by parametric fitting of sensor responses

This study describes a novel method for characterizing the colorimetric and photometric properties of three‐channel color imaging devices. The method is designed to overcome some undocumented aspects of the imager‐characterization problem: The effective spectral sensitivity profiles of the imager's color channels depend on the level of radiant input energy, and these profiles must be known in order to determine the true intensity‐response characteristics of the three channels. By fitting the response distributions of the three color channels explicitly with low‐dimensional models, the method takes these dependencies into account, and may, therefore, offer several advantages over other imager‐characterization methodologies, particularly where illuminant‐independent characterization is required. An application of the technique is detailed, in which a CCD camera is characterized using only the Macbeth ColorChecker and a number of artificial illuminants. © 2001 John Wiley & Sons, Inc. Col Res Appl, 26, 442–449, 2001