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     

Testing the robustness of CIECAM02

CIE TC8‐01 has adopted a new color appearance model: CIECAM02¹ replaces the CIECAM97s.² The new model consists of a number of refinements and simplifications of the CIECAM97s color appearance model. This article describes further tests to the robustness of the forward and reverse modes. © 2005 Wiley Periodicals, Inc. Col Res Appl, 30, 99–106, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20087     

ICC印刷流程中感知映射意图评价

一场对于ICCv2和v4感知映射意图参考色域的视觉评估实验在Bonnier等人前期实验的基础上展开了。实验的目的在于评估sRGB v2和v4中感知映射意图在ICC打印工作流的表现。用于评估的文件包括ISO标准sRGB图像,所有图像均从一台色域范围中等打印机输出,承印介质为普通打印纸。实验邀请到了两组评估人员,专业评估组均为经验丰富的图像质量评估人员,或为色彩学研究人员,普通评估组由未曾接触过图像质量评估的人员组成,所有人员均有正常的色彩视觉感知。实验结果显示,ICC v4打印工作流在总体上优于v2版本,但从偏好性和复制准确性来看,所有测试的打印工作流没有同时满足这两项要求;从评估者本身来分析,专业评估组对于图像质量的判断从自身一致性和同批一致性上均优于普通评估组,偏好性实验的结果与前期Bonnier等人的实验结果一致。     

Black‐level offset: Characterization and correction

Abstract— The correct setting of the black level is an important step in the (re)calibration of an electronic display. This study looks at the consequences of black‐level offset, the possibilities for display characterization with offset, offset correction, and the ability of average untrained users to visually correct the black‐level setting with the contrast and brightness controls on the display. In an experiment, 32 subjects were asked to optimally set the black level according to two types of instructions (short and extensive, between subjects) under two levels of illumination (low and office, between subjects) for two types of displays (CRTs and LCDs, within subjects). Most subjects were not able to set the black level near optimal for either display, with any combination of instruction and illumination level. The LCD did not have an optimal black level. For the CRT, optimal black level did not provide minimal differences with the sRGB standard tone reproduction curve.     

基于Web的彩色管理解决方案

彩色管理是近几年新发展起来的颜色复制与传递技术,广泛应用于桌面电子出版系统（ＤＴＰ）。随着Ｉｎｔｅｒｎｅｔ的发展,该技术被逐渐引入Ｗｅｂ应用领域。该文在表明了目前在电子商务中存在的色彩问题之后,阐述了基于Ｗｅｂ的彩色管理解决方案。     

Proposal for selecting two‐color combinations with various affections. Part II: Demonstration of the system

The characteristics of the proposed color selection system are shown using several colored figures of two‐color combinations selected by the system. There are four kinds of color feelings in the system, and each feeling is classified into three categories (i.e., high, intermediate, or low). The feelings used are pleasantness, contrast, floridness, and warmth. Users can try the 3⁴ = 81 combinations of feelings by setting the categories for four kinds of feelings. The differences among categories of color feelings are also shown by several colored figures. It is difficult to describe the differences by words. However, it is rather easy to describe by pictures. The proposed color selection system is expected to be a useful tool for assisting color designers. Comments about the proposed system from potential users are reported. © 2009 Wiley Periodicals, Inc. Col Res Appl, 34, 135–140, 2009     

Recovering spectral reflectance based on natural neighbor interpolation with model‐based metameric spectra of extreme points

In this article, we proposed a new method based on natural neighbor interpolation to recover the spectral reflectance of objects from an image captured by a traditional Red‐Green‐Blue (RGB) digital camera. The concept of model‐based metameric spectra of eight extreme points in the standard RGB (sRGB) color gamut was further introduced to ensure that almost all test samples in the entire gamut can be simply and properly recovered without needing the extrapolation or any other auxiliary techniques. The quasi‐Newton method was used to estimate iteratively the optimal parameters of these metameric spectra, satisfying the constraints of the gamut extreme points. Several experiments were performed. The effectiveness of the method with and without the metameric spectra was evaluated, including some performance comparisons with the principal component analysis (PCA) method of transformational type (classic PCA and weighted PCA) and that of interpolation type. The results showed that the proposed method greatly enlarged the accurately applicable domain of the interpolation strategy and offered spectra with feasibility and naturalness much superior to the PCA‐based methods. The proposed method was obviously better than the conventional interpolation ones, and had a similar performance with the weighted PCA method in terms of color difference.     

Visual gamma measurement and methods to compare gamma models

Abstract— The correct estimation of the gamma exponent describing the tone‐reproduction curve of a display is an important step in color management. Several methods for visual gamma estimation have been proposed. In this study, the theoretical merits and practical problems of a number of these methods are discussed and compared, and improvements are suggested. A new method to compare gamma models with different numbers of parameters is introduced. In an experiment, spatial and temporal brightness‐matching methods were tested with 32 untrained subjects working on a CRT and an LCD with different resolutions under office and low‐illumination conditions. Illumination had no effect on gamma estimations. Subjects had great difficulties with spatial brightness matching at low resolutions. Temporal and spatial visual brightness matching for untrained subjects showed a larger gamma than photometric fits.     

A revision of the CIECAM97s model

The CIECAM97s model was adopted by the CIE in 1997 for colour imaging applications. It includes forward and reverse modes. Some problems in using this model were found in recent field trials. This article suggests revision to the model in two respects: (a) to make the lightness (J) zero when the Y tristimulus value is zero, under all surround conditions; (b) to modify the chromatic induction factor (Nc) from 1.10 to 0.95 for the dim surround condition. To avoid confusion, it is suggested that the revised version of the model be designated CAM97s2. The article also describes an alternative mode to achieve a more nearly exact reversibility between the forward and reverse modes. © 2000 John Wiley & Sons, Inc. Col Res Appl, 25, 260–266, 2000     

Improving color reproduction accuracy of an OLED‐based mobile display

For improving color reproduction accuracy of mobile displays, we recently developed a generic model for device‐specific display characterization model that also accounts for the influence of illuminance from ambient light. In the present article, this MDCIM model (Mobile Display Characterization and Illumination Model) is applied to a Samsung Galaxy S4 display, representing OLED displays. The performance of the model was tested by determining the values of all model parameters using publicly available technical data only. We organized visual tests under various ambient illuminance levels from 600 to 3000 lux. Seven observers compared the color of displayed images with the color of physical samples. With the MDCIM method, the quality of the color match was shown to improve considerably as compared to using only device‐independent encoding color space. On a five‐point scale to quantify color reproduction accuracy, the MDCIM resulted in more than 1 unit improvement at 1000 lux illuminance. At lower and higher illuminance, the improvement was even larger. Color reproduction accuracy was found to be at least reasonable, according to the subjective assessment of visual observers, for more than 75% of the samples when using the MDCIM method, but only 20% or less when using the common device‐independent encoding color space.