Evaluating gamut mapping algorithms for universal applicability

The aim of this article is to present the evaluation of gamut mapping algorithms (GMAs) in a series of three experiments intended to serve as the basis for developing solutions that are accurate and universally applicable. An evolutionary gamut mapping development strategy is used, in which five test images are reproduced between a CRT and printed media obtained using different GMAs. Initially, a number of previously published algorithms were chosen and psychophysically evaluated, whereby an important characteristic of this evaluation was the separate evaluation for individual colour regions within test images. New algorithms were then developed on this experimental basis, subsequently evaluated, and the process was repeated once more. In this series of experiments, the new GCUSP algorithm, which consists of a chroma‐dependent lightness compression followed by a compression towards the lightness of the reproduction cusp on the lightness axis, gave the most accurate and stable performance overall. The results of these experiments were also useful for improving the understanding of some gamut mapping factors—in particular gamut difference between media. © 2001 John Wiley & Sons, Inc. Col Res Appl, 26, 85–102, 2001     

Color gamut mapping based on a perceptual image difference measure

Gamut mapping is a color transformation technique to solve a problem caused by mismatch of gamuts among imaging devices. One plausible goal of gamut mapping is to find a reproduction that is perceptually closest to the corresponding original image when an exact color matching is not possible. Several measures to quantify the perceptual difference between images have been proposed and applied to the gamut mapping problem. However most of the measures, such as average color difference, are applied on a pixel‐wise basis and show poor correlation with human visual perception. This article describes a model of the perceptual image difference for a given pair of images, which takes the human's contrast sensitivity into account and applies the model to a gamut mapping for generating a reproduction with minimum perceptual image difference. The model has a multispatial‐frequency channel structure with tunable peak gains for each channel, which are determined by psychophysical experiments, so that the model output fits the observer's sensitivity to the image difference. A gamut‐mapped image with minimum perceptual image difference is obtained by an iterative minimization process. To evaluate the proposed method, subjective evaluation experiments are performed to construct ratio scales that measure perceptual image difference of gamut‐mapped reproductions generated by the proposed and pixel‐wise methods. Results show that the reproductions by the proposed method are perceived as perceptually closest to the original, and the model's estimate of perceptual difference correlates better with the experimentally measured perceived image difference than other pixel‐wise measures. © 1999 John Wiley & Sons, Inc. Col Res Appl, 24, 280–291, 1999     

Brighter,more colorful colors and darker,deeper colors based on a theme of brilliance

A methodology for achieving brighter, more colorful colors and deeper, darker colors based on Evans' zero gray (G₀) [described in The Perception of Color] and his concept of brilliance as a percept in color vision was demonstrated and tested psychometrically in media produced under current digital video and digital cinema standards—basically the sRGB set of primaries. Objects or surfaces in a scene represented in sRGB as having gray content in the Evans sense are rendered as original. Flesh tones are preserved. Those features not having gray content—a highly colorful arrangement of flowers, a clear blue sky, and the glossy red lipstick of a beautiful lady—are made brighter, more colorful and deeper, darker when rendered in a set of primaries that emulate, for example, the xvYCC‐encoded standard and whose colors extend beyond those of sRGB—an expanded gamut, if you will. In all but the most‐aggressive application, versions of scenes where this methodology was applied were consistently preferred over the sRGB version across 10 representative scenes and 17 observers. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2010     

Gamut mapping from below: Finding minimum perceptual distances for colors outside the gamut volume

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     

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     

Development and evaluation of gamut extension algorithms

In recent years, new display technologies have emerged that are capable of producing colors that exceed the color gamut of broadcast standards. On the other hand, most video content currently remains compliant with the EBU standard and as such, there is a need for color mapping algorithms that make optimal use of the wider gamut of these new displays. To identify appropriate color mapping strategies, we have developed, implemented, and evaluated several approaches to gamut extension. The color rendering performance and robustness to different image content of these algorithms were evaluated against a reference (true‐color) mapping. To this end, two psychophysical experiments were conducted using a simulated and actual wide‐gamut display. Results show that the preferred algorithm had a dependency on image content, especially for images with skin tones. In both experiments, however, there was preference shown for the algorithm that balances chroma and lightness modulations as a function of the input lightness. The newly designed extension algorithms consistently outperformed true‐color mapping, thus confirming the benefit of appropriate mapping on wide‐gamut displays. © 2009 Wiley Periodicals, Inc. Col Res Appl, 34, 443–451, 2009     

Preferred color gamut boundaries for wide‐gamut and multiprimary displays

Preferred chroma enhancement and its dependence on hue are studied in a two‐part experiment using a wide‐gamut multiprimary display. Earlier research showed a clear dependence on hue but was limited by the gamut of the display it employed; the present work builds on this while easing the gamut constraints. In the first part of the present experiment, a tuning task was used to refine the preference for chroma boost starting with standard‐gamut (Rec. 709) images. The overall median preferred boost is roughly 20%, but it is not uniform over hues: the preferred boost for orange, yellow, green, and cyan colors is greater than that for blue, magenta, and red colors. Dependence on image content and observer is noted, though a content‐independent chroma boost created by aggregating preference over many images performs well. An adjustment parameter for overall chroma, which incorporates the hue dependence averaged over image content, should be sufficient to handle the vast majority of interobserver variance in preference. In the second part of the experiment, various chroma boost algorithms were evaluated through a paired comparison task. The prescribed hue‐dependent chroma boost is preferred over all other variations, and all hue‐preserving chroma boost variations are preferred over both colorimetrically accurate and na??ve same‐drive‐signal renderings. The results may be applied in display design to select gamut boundaries that maximize satisfaction over the observer population. © 2012 Wiley Periodicals, Inc. Col Res Appl, 39, 169–178, 2014     

A novel Color Rendition Chart for digital tongue image calibration

Digital tongue images are usually acquired by a camera under specific illumination environments. In order to guarantee better color representation of the tongue body, we propose a novel tongue Color Rendition Chart acting as a color reference to be used in color calibration algorithms to standardize the captured tongue images. First, based on a large tongue image database captured with our digital tongue image acquisition system, we establish a statistical tongue color gamut. Then, from the first step, different quantities of colors in the Color Rendition Chart are determined via experimentation. Afterwards, results using X‐Rite's ColorChecker® Color Rendition Chart (a standard in the color calibration field) are compared with the proposed tongue Color Rendition Chart by applying the color difference calculation formula of CIELAB and CIEDE2000 as a reference for the mean color calibration error. The results show that the proposed tongue Color Rendition Chart, which has 24 colors, produces a much smaller error (CIELAB —8.0755/CIEDE 2000—6.3482) compared with X‐Rite's ColorChecker® Color Rendition Chart (CIELAB 1976—14.7836/CIEDE 2000—11.7686). This demonstrates the effectiveness of the novel tongue Color Rendition Chart.     

Try camera gamut again: Not for size,but for camera and profile evaluation

Hunt and Pointer call into question the utility of the camera color gamut (at least by my definition). Such doubt may be partly due to the connection of gamut with a size metric. Quite apart from gamut size, the sets that define my gamut definition are essential to the evaluation of digital cameras in conjunction with their profiles. The output‐device gamut; emphasized by Hunt and Pointer is also important, but appears at another stage of color management. © 2007 Wiley Periodicals, Inc. Col Res Appl, 33, 82–83, 2008     

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     

Spectral color reproduction minimizing spectral and perceptual color differences

In this article, we are combining minimization criteria in the colorant separation process for spectral color reproduction. The colorant separation is performed by inverting a spectral printer model: the spectral Yule‐Nielsen modified Neugebauer model. The inversion of the spectral printer model is an optimization operation in which a criterion is minimized at each iteration. The approach we proposed minimizes a criterion defined by the weighted sum of a spectral difference and a perceptual color difference. The weights can be tuned with a parameter α ∞ [0, 1]. Our goal is to decrease the spectral difference between the original data and its reproduction and also to consider perceptual color difference under different illuminant conditions. In order to find the best α value, we initially compare a pure colorimetric criterion and a pure spectral criterion for the reproduction, then we combine them. We perform four colorant separations: the first separation will minimize the 1976 CIELAB color difference where four illuminants are tested, the second separation will minimize an equally weighted summation of 1976 CIELAB color difference with the four illuminants tested independently, the third colorant separation will minimize a spectral difference, and the fourth colorant separation will combine a weighted sum of a spectral difference and one of the two first colorimetric differences previously introduced. This last colorant separation can be tuned with a parameter in order to emphasize on spectral or colorimetric difference. We use a six colorants printer with artificial inks for our experiments. The prints are simulated by the spectral Yule‐Nielsen modified Neugebauer model. Two groups of data are used for our experiments. The first group describes the data printed by our printing system, which is represented by a regular grid in colorant space of the printer and the second group describes the data which is not originally produced by our printing system but mapped to the spectral printer gamut. The Esser test chart and the Macbeth Color Checker test chart have been selected for the second group. Spectral gamut mapping of this data is carried out before performing colorant separation. Our results show improvement for the colorant separations combining a sum of 1976 CIELAB color difference for a set of illuminants and for the colorant separation combining a sum of 1976 CIELAB color difference and spectral difference, especially in the case of spectral data originally produced by the printer. © 2008 Wiley Periodicals, Inc. Col Res Appl, 33, 494–504, 2008     

Repairing gamut problems in CIECAM02: A progress report

The color‐appearance model CIECAM02 has several problems, which can result in mathematical instabilities, due to the position of the chromatic‐adaptation primaries relative to the spectrum locus and to the presumed physiological cone primaries. To keep a corresponding (adapted) color within the positive gamut given by the chromatic adaptation primaries, the gamut must lie within the cone primary octant. To contain adapted colors within the positive cone‐primary octant, it suffices to truncate the action of adaptation at the boundary of that octant. Such modifications may be needed to avoid the mathematical problems in CIECAM02. © 2008 Wiley Periodicals, Inc. Col Res Appl, 33, 424–426, 2008     

Suggested optimum primaries and gamut in color imaging

Suggested optimal “primaries” and concomitant optimal gamut for any form of device or product whose output serves as input to the normal human visual system: TV‐like images, or images reflected from illuminated hardcopy. For those devices and products using additive coloration, three spectral primaries 450–530–610 nm, and their associated gamut, are suggested as goals. For those using subtractive coloration, three reflective components, of width perhaps 50–60 nm at half‐height and peaking at the same wavelengths, are suggested. Thus, in either case, the light from each pixel of the generated color image entering the pupil of the normal human observer is composed of a mixture of that observer's prime colors. “Prime colors” are defined as usual as (a) the wavelengths marking the peaks of the three spectral sensitivities of the (trichromatic) normal human visual system, and, thus, (b) those spectral lights to which the normal human visual system responds most strongly per watt of power content input to the pupil. Spectral sensitivities of the normal human visual system are carefully distinguished from those of the CIE Standard Observers. © 2000 John Wiley & Sons, Inc. Col Res Appl, 25, 148–150, 2000     

Comparison of real colour gamuts using a new reflectance database

A large set of data, comprising the spectral reflectances of real surface colours, has been accumulated. The data comprise 16 groups with different materials and include 85,879 measured spectra. From these data, CIELAB colorimetric coordinates were calculated under CIE illuminant D50 and the CIE 1931 standard colorimetric (2°) observer. Several published colour gamuts including those developed by Pointer and ISO reference colour gamut [ISO Graphic Technology Standard 12640‐3:2007] were compared using the present data set. It was found that the Pointer gamut is smaller than the new real data in most of the colour regions. The results also showed that the ISO reference colour gamut is larger than the new real accumulated data in most regions. The present finding indicates that there is a need to derive a new colour gamut based on the newly accumulated data for common applications. © 2013 Wiley Periodicals, Inc. Col Res Appl, 39, 442–451, 2014     

Evaluation of expanded gamut software solutions for spot color reproduction

Expanded gamut printing is an approach in color reproduction that expands the color gamut of conventional CMYK printing processes via the use of additional colorants, such as Orange, Green, and Violet inks. This study evaluates the ability of commercial color management software to create an accurate solution for an expanded gamut printing system. In this study, two printing processes were used, an Epson SureColor P9000 inkjet printer/proofer and an HP Indigo 7900 digital production press, both with 7-color expanded gamut ink sets. Software solutions from Alwan, CGS ORIS, ColorLogic, GMG Color, Heidelberg, and Kodak were evaluated. The systems were tested to see how well they could reproduce the colors in the entire PANTONE+ Solid Coated spot color library. It is shown that the solutions are able to reproduce 89% to 94% of the spot colors on the Epson P9000 inkjet printer and 77% to 87% of the library on the Indigo 7900, both to less than two CIEDE2000 (a typical tolerance in label and packaging work). The number of color patches in expanded gamut characterization test charts was noted, as this is still an area of proprietary, nonstandardized working practice. There are many different colorant combinations that can make the same color in expanded gamut printing. The ink build created by the different software solutions was studied, as it relates to press stability through appropriate choice of colorants. Pantone and Adobe provide everyday commercial tools for expanded color workflows. The study identified some issues with products from these companies that could confuse a less-skilled user in a busy production environment. The conclusion of the study is that expanded gamut solutions for spot color printing produce totally acceptable results for digital printing processes; expanded gamut printing is ready, here and now. The findings show that expanded gamut printing can replace cumbersome conventional spot color workflows creating considerable savings and advantages, especially for label and packaging printers.