Visual evaluation at scale of threshold to suprathreshold color difference

Visual evaluation experiments of color discrimination threshold and suprathreshold color‐difference comparison were carried out using CRT colors based on the psychophysical methods of interleaved staircase and constant stimuli, respectively. A large set of experimental data was generated ranged from threshold to large suprathreshold color difference at the five CIE color centers. The visual data were analyzed in detail for every observer at each visual scale to show the effect of color‐difference magnitude on the observer precision. The chromaticity ellipses from this study were compared with four previous published data, of CRT colors by Cui and Luo, and of surface colors by RIT‐DuPont, Cheung and Rigg, and Guan and Luo, to report the reproducibility of this kind of experiment using CRT colors and the variations between CRT and surface data, respectively. The present threshold data were also compared against the different suprathreshold data to show the effect of color‐difference scales. The visual results were further used to test the three advance color‐difference formulae, CMC, CIE94, and CIEDE2000, together with the basic CIELAB equation. In their original forms or with optimized K_L values, the CIEDE2000 outperformed others, followed by CMC, and with the CIELAB and CIE94 the poorest for predicting the combined dataset of all color centers in the present study. © 2005 Wiley Periodicals, Inc. Col Res Appl, 30, 198–208, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20106     

Forgotten pioneers of color order. Part I: Gaspard Grégoire (1751–1846)

Some 100 years before Albert Munsell developed his color order system, French silk merchant and inventor of a technology for producing works of art in silk velours, Gaspard Grégoire, introduced a color order system based on the color attributes hue, (relative) chroma, and lightness. Conceived in the mid‐1780s, an atlas with 1350 samples was produced before 1813 and found use in French Royal manufacturing operations and educational institutions. It was followed a few years later by one with 343 samples. Grégoire's work was subsequently overshadowed by Michel‐Eugene Chevreul's more complicated and less intuitive hemispherical system of 1839. © 2007 Wiley Periodicals, Inc. Col Res Appl, 33, 5–9, 2008     

Note on ‘Construction of Double Sampling s‐Control Charts for Agile Manufacturing’

He and Grigoryan (Quality and Reliability Engineering International 2002; 18 :343–355) formulated the design of a double‐sampling (DS) s control chart as an optimization problem and solved it with a genetic algorithm. They concluded that the DS s control charts can be a more economically preferable alternative in detecting small shifts than traditional s control charts. We explain that, since they only considered the average sample size when the process is in control, their conclusion is questionable. Copyright © 2006 John Wiley & Sons, Ltd.     

Evaluation of image similarity by histogram intersection

Colour is the most widely used attribute in image retrieval and object recognition. A technique known as histogram intersection has been widely studied and is considered to be effective for color‐image indexing. The key issue of this algorithm is the selection of an appropriate color space and optimal quantization of the selected color space. The goal of this article is to measure the model performance in predicting human judgment in similarity measurement for various images, to explore the capability of the model with a wide set of color spaces, and to find the optimal quantization of the selected color spaces. Six color spaces and twelve quantization levels are involved in evaluating the performance of histogram intersection. The categorical judgment and rank order experiments were conducted to measure image similarity. The CIELAB color space was found to perform at least as good as or better than the other color spaces tested, and the ability to predict image similarity increased with the number of bins used in the histograms, for up to 512 bins (8 per channel). With more than 512 bins, further improvement was negligible for the image datasets used in this study. © 2005 Wiley Periodicals, Inc. Col Res Appl, 30, 265–274, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20122     

Electrochemical Aspects of Electroosmotic Dewatering of Clay Suspensions

An attempt is made to elucidate the electrochemical aspects of the electroosmotic dewatering (EOD) of clays as reported in some recent work, especially that on interrupted DC power electroosmotic dewatering published by Rabie, Mujumdar and Weber (2). These authors showed that the dewatering by EOD stops after the DC power has been on for several minutes or hours; on interruption of their power and on short-circuiting of the electrodes, conditions can be created again for some further dewatering by DC power EOD. This discovery, of Rabie et al. is interpreted as a fuel cell effect and it is shown that it affords clues to several other electrochemical strategies for the possible enhancement of the efficiency of the EOD by DC power.

Further, the open circuit potentials observed by Rabie et al. (2) on the interruption of DC power are given an electrochemical interpretation which leads to quantitative estimates in agreement with the experimental values.     

新取代苯基荧光酮试剂的合成及其性质的研究Ⅱ．新型取代苯基荧光酮与金属离子显色反应的研究

研究了３，５－二溴－４－氨基苯基荧光酮、３，５－二溴－４－偶氮变色酸等８种苯基荧光酮在酸性介质中与高价金属离子Ｚｒ（Ⅳ）、Ｍｏ（Ⅵ）、Ｗ（Ⅵ）、Ａｌ（Ⅲ）、Ｇａ（Ⅲ）等的显色反应。３，５－位二溴取代的试剂的灵敏度高于未取代的灵敏度，摩尔吸光系数绝大多数在１０５Ｌ·ｍｏｌ－１·ｃｍ－１以上。     

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     

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     

Effects of surrounding brightness on visual search for safety colors

The present article reports the investigation of the effects of surrounding brightness on a visual search for three safety colors: red, orange, and yellow. Images of visual stimuli consisting of an array of colored circles placed on a large visual field (a visual angle of 40°) were displayed on an 80‐in. screen with a DLP projector. Experiment I examined the search efficiency under three levels of background luminance that were equivalent to the three target luminances. The results showed that the search efficiency for the orange target decreased as the number of distractors increased, under each of the background luminance levels, whereas the efficiency scarcely decreased for the red and yellow targets. Although a reduction in background luminance increased the search efficiency for the orange target, it is suggested that the effect of background luminance is smaller than the effect of the target color in search efficiency. Experiment II examined the search efficiency under three conditions of low levels of incident illuminance, which were matched with a linear regression to the luminance of color chips of safety colors measured twilight conditions. The results showed that the search efficiency for the orange target decreased as the number of distractors increased under each of the different illuminance conditions, whereas the efficiency scarcely decreased for red and yellow targets. Furthermore, as illuminance decreased, the search time for the orange target was more greatly impacted than for red or yellow. These results imply that the recognition of orange tends to be influenced by the surrounding brightness. © 2005 Wiley Periodicals, Inc. Col Res Appl, 30, 400–409, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20152