Camera color analysis gamut

Michael Brill has opened a valuable discussion about camera gamuts and Roy Berns has questioned the use of the word “gamut” in that proposal. We would like to stress the importance of associating a gamut with an imaging output device and would thus question the use of the concept proposed for assessing the capabilities of an input device. © 2007 Wiley Periodicals, Inc. Col Res Appl, 33, 81–82, 2008     

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     

Expanding display color gamut beyond the spectrum locus

Digital video and display media are at a “sweet spot” of growth with brighter and more colorful digital projectors and displays available seemingly every day. Much more is possible in achieving brighter and more vibrant colors, colors that may even transcend our typical experience in terms of dynamic range and an expanded gamut in the perceptual sense. If the full capabilities of these technologies to produce a fuller visual experience are to be realized, new processing and encoding methodologies are required. In this article, the powers of adaptation and the CIECAM02 color appearance model are exploited to define perceptual gamut. The strategy of this methodology is, simply and in effect, to “push down” the white point of the display and demonstrate, both empirically and with a limited set of images, a striking gamut expansion in the perceptions of lightness, chroma, brightness, and colorfulness beyond the locus of pure, spectral color, and the MacAdam limits as observed with traditional display configurations. © 2006 Wiley Periodicals, Inc. Col Res Appl, 31, 475–482, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20260     

Perceptual evaluation of color gamut mapping algorithms

The recommendation of the CIE has been followed as closely as possible to evaluate the accuracy of five color gamut mapping algorithms (GMAs)—two nonspatial and three spatial algorithms—by psychophysical experiments with 20 test images, 20 observers, one test done on paper and a second one on display. Even though the results do not show any overall “winner,” one GMA is definitely perceived as not accurate. The importance of a high number of test images to obtain robust evaluation is underlined by the high variability of the results depending on the test images. Significant correlations between the percentage of out‐of‐gamut pixels, the number of distinguishable pairs of GMAs, and the perceived difficulty to distinguish them have been found. The type of observers is also important. The experts, who prefer a spatial GMA, show a stronger consensus and look especially for a good rendering of details, whereas the nonexperts hardly make a difference between the GMAs. © 2008 Wiley Periodicals, Inc. Col Res Appl, 33, 470–476, 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     

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.     

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     

The effects of functional polysiloxane resins on the color gamut and color yield of dyed polyester

It is important to evaluate the influence of textile finishing using the polymer resins on the color of dyed fabrics. In this article, three functional polysiloxanes modified with different organic groups were used to treat dyed polyester microfiber fabrics. Effects of the polysiloxanes on the color of the dyed polyester were investigated by color yield (K/S), colorimetric data of CIELAB, and the color differences (ΔE). Chemical structures of three functional polysiloxanes were the polysiloxanes with amino groups (polymer A), with perfluorocarbon groups (polymer B), or with quaternary ammonium salts and perfluorocarbon groups (polymer C). Compared with the dyed fabrics treated with the polysiloxane with amino group, the K/S of dyed fabrics treated with the polysiloxane with perfluorocarbon obviously improved. Effects of the polysiloxanes with perfluorocarbon and cationic groups on the color shade of the dyed polyester were noticeable. The fastness had not significantly changed. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2012     

Image quality evaluation for high dynamic range and wide color gamut applications using visual spatial processing of color differences

High dynamic range (HDR) and wide color gamut imagery has an established video ecosystem, spanning image capture to encoding and display. This drives the need for evaluating how image quality is affected by the multitudes of ecosystem parameters. The simplest quality metrics evaluate color differences on a pixel‐by‐pixel basis. In this article, we evaluate a series of these color difference metrics on four HDR and three standard dynamic range publicly available distortion databases consisting of natural images and subjective scores. We compare the performance of the well‐established CIE L*a*b* metrics (ΔE₀₀ , ΔE₉₄ ) alongside two HDR‐specific metrics (ΔE_Z [J_za_zb_z], ΔE_ITP [IC_TC_P]) and a spatial CIE L*a*b* extension (). We also present a novel spatial extension to ΔE_ITP derived by optimizing the opponent color contrast sensitivity functions. We observe that this advanced metric, , outperforms the other color difference metrics, and we quantify the improved performance with the steps of metric advancement.     

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     

Let's call it “color‐gamut rendering”

The term “color gamut” historically has been associated with color output such as optimal color stimuli and additive and subtractive imaging systems. Recently, this term has been used with input devices such as scanners and digital cameras. It is proposed that the term “color‐gamut rendering” should be used instead of input devices. This clarifies the distinction between input (analysis) and output (synthesis) color systems in terms of the effect of an input system on defining the colorimetric properties of an output system. © 2007 Wiley Periodicals, Inc. Col Res Appl, 32, 334–335, 2007     

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     

Extending the color gamut and dynamic range of an sRGB image using a residual image

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     

Optimization of quinacridone magenta,Cu-phthalocyanine cyan,and arylide yellow ink films formulated for maximum color gamut

Investigation of ink formulation options with the purpose to obtain color-gamut-optimal set of Cyan Magenta and Yellow CMY inks is reported. Implementation of the thickness dependent Kubelka-Munk model on multiple ink layers having different and well-defined thicknesses, provides characteristic absorption and scattering (K, S ) spectra of the ink ingredients. These data enable accurate computation of the reflectance spectrum and thus the L*a*b* color coordinates for any given ink thickness or substrate. Pigment materials investigated are quinacridone as magenta, copper-phthalocyanine as cyan, and arylide yellow. Scaling the peak of the absorption band to the number of molecules per unit area for the specific pigments studied in this article provides the molar extinction coefficients, 1.21 × 10⁴ , 4.7 × 10⁴ , and 3.3 × 10⁴ cm²/millimole respectively, regardless of the different ink formulations used, in accord with Avogadro's principle. Having a set of three pairs of K, S spectra is used to compute the color gamut of any CMY color combination in the L*a*b* space as a function of ink layer thickness and formulation. Using an iterative algorithm, a color-gamut-optimal set of CMY inks is obtained.     

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     

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