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     

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     

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     

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     

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     

多笔画青色文字感知清晰度模型研究

建立了多笔画青色文字感知清晰度模型。针对多笔画文字,选择常用的6．5磅和10．5磅字号黑体,用喷墨打印机分别在具有代表性的16种打印纸上输出。基于ISO13660标准中的线条属性,选取了最能体现文字清晰度的属性指标;通过观察者的主观评价及与属性指标的数学关联,建立了多笔画青色字体感知清晰度的评价模型。结果表明,多笔画青色字体的感知清晰度与文字线条的对比度、粗糙度、模糊度和线宽都相关。其中,对比度对感知清晰度的影响最大,且正相关,对比度越大,感知清晰度越高。而粗糙度、模糊度、线宽与字体的感知清晰度成负相关,字体感知清晰度随着粗糙度、模糊度或线宽的增加,都会有一定程度的降低。     

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     

Color separation for improved perceived image quality in terms of graininess and gamut

Multi‐channel printing employs additional inks to improve the perceived image quality by reducing the graininess and augmenting the printer gamut. It also requires a color separation that deals with the one‐to‐many mapping problem imposed when using more than three inks. The proposed separation model incorporates a multilevel halftoning algorithm, reducing the complexity of the print characterization by grouping inks of similar hues in the same channel. In addition, a cost function is proposed that weights selected factors influencing the print and perceived image quality, namely color accuracy, graininess and ink consumption. The graininess perception is qualitatively assessed using S‐CIELAB, a spatial low‐pass filtering mimicking the human visual system. By applying it to a large set of samples, a generalized prediction quantifying the perceived graininess is carried out and incorporated as a criterion in the color separation. The results of the proposed model are compared with the separation giving the best colorimetric match, showing improvements in the perceived image quality in terms of graininess at a small cost of color accuracy and ink consumption. © 2016 Wiley Periodicals, Inc. Col Res Appl, 42, 486–497, 2017     

基于模糊聚类的彩色图像分割算法

提出了基于HSV空间的模糊聚类彩色图像分割算法。运用模糊C方法（FCM fuzzy clustering measure模糊聚类方法）对颜色量化后的图像进行聚类,结合了彩色图像的色彩和空间信息的特点,并且对聚类结果进行了合并优化,去除了聚类过于细小的部分。     

Derivation of a color space for image color difference measurement

In digital image reproduction, it is often desirable to compute image difference of reproductions and the original images. The traditional CIE color difference formula, 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 preprocessing 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 [IS&T/SID 10th Color Imaging Conference, 2002; 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 tristimulus values or approximate human cone responses (LMS), and then further transformed into opponent‐color channels approximating white‐black, red‐green, and yellow‐blue color perceptions. Once in the opponent space, the images are filtered with approximations of human contrast 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 difference calculations, the ideal opponent color space would be both linear and orthogonal such that the linear filtering 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, 2010     

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     

基于小波理论的图像压缩算法

运用小波变换的多分辨特点 ,研究了基于小波的图像压缩技术。利用人眼特性 (HVS) ,提出了分块压缩算法。该算法利用小波系数子带的相关性 ,从而在同样的平均码率下 ,获得了主观感觉较好的重构图像 ,也就是说在同样的主观条件上得到更大的压缩比。另外利用工具软件MATLAB对算法进行了实施 ,结果证明了该算法的有效性。     

涤纶纱线和织物的色差影响因素和控制措施探讨

探讨了涤纶纤维染色机理和色差评价方法,初步分析了涤纶纱线、织物在聚酯合成、纺丝以及纺织染整过程中存在的色差影响因素,并提出了控制色差的有效措施。     

基于图像技术的化学需氧量检测研究

为了准确、快速分析水质中化学需氧量(COD),在分光光度法基础上,提出根据图像颜色特征值测量COD的方法 ,同时开发了基于图像技术的检测装置。以该装置为平台,进行了水质COD测定条件的优选,并在优选条件下建立最佳颜色特征值与COD浓度的关系模型。最后进行重复性检测和测量结果对比分析。结果表明:该方法相关系数R~2=0.995 26,检测范围为40~550 mg/L。该装置比国标法和快速法测COD操作简便,并具有较高的准确性。