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1.
Colour remains one of the key factors in presenting an object and, consequently, has been widely applied in retrieval of images based on their visual contents. However, a colour appearance changes with the change of viewing surroundings, the phenomenon that has not been paid attention yet while performing colour‐based image retrieval. To comprehend this effect, in this article, a chromatic contrast model, CAMcc, is developed for the application of retrieval of colour intensive images, cementing the gap that most of existing colour models lack to fill by taking simultaneous colour contrast into account. Subsequently, the model is applied to the retrieval task on a collection of museum wallpapers of colour‐rich images. In comparison with current popular colour models including CIECAM02, HSI and RGB, with respect to both foreground and background colours, CAMcc appears to outperform the others with retrieved results being closer to query images. In addition, CAMcc focuses more on foreground colours, especially by maintaining the balance between both foreground and background colours, while the rest of existing models take on dominant colours that are perceived the most, usually background tones. Significantly, the contribution of the investigation lies in not only the improvement of the accuracy of colour‐based image retrieval but also the development of colour contrast model that warrants an important place in colour and computer vision theory, leading to deciphering the insight of this age‐old topic of chromatic contrast in colour science. © 2014 Wiley Periodicals, Inc. Col Res Appl, 40, 361–373, 2015 相似文献
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Paulo S. André António L. Teixeira Armando N. Pinto Lara P. Pellegrino Berta B. Neto José F. Rocha Joäo L. Pinto Paulo N. Monteiro 《ETRI Journal》2006,28(2):257-259
In this letter, we will evaluate the performance degradation of a 40 km high‐speed (40 Gb/s) optical system, induced by optical fiber variations of the chromatic dispersion induced by temperature changes. The chromatic dispersion temperature sensitivity will be estimated based on the signal quality parameters. 相似文献
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Ralph W. Pridmore 《Color research and application》2008,33(1):77-81
In present convention, chromatic induction (simultaneous and successive contrast) is usually held to be an opponent color process. Fifty years ago, it was an accepted complementary color process. The latter was never disputed yet apparently overlooked, and is here shown to be the more accurate account by inspecting afterimages and published data on simultaneous and successive hue induction. © 2007 Wiley Periodicals, Inc. Col Res Appl, 33, 77–81, 2008 相似文献
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计算机配色技术应用于木材染色初探 总被引:1,自引:0,他引:1
介绍了计算机测色配色系统的原理,研究了建立木材染色基础数据库的方法,提出了注意事项,并分析了自动配色过程中产生色差的原因及解决方法。 相似文献
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Ralph W. Pridmore 《Color research and application》2007,32(6):469-476
Chromatic luminance (i.e., luminance of a monochromatic color) is the source of all luminance, since achromatic luminance arises only from mixing colors and their chromatic luminances. The ratio of chromatic luminance to total luminance (i.e., chromatic plus achromatic luminance) is known as colorimetric purity, and its measurement has long been problematic for nonspectral hues. Colorimetric purity (pc) is a luminance metric in contrast to excitation purity, which is a chromaticity‐diagram metric approximating saturation. The CIE definition of pc contains a fallacy. CIE defines maximum (1.0) pc for spectral stimuli as monochromatic (i.e., optimal) stimuli, and as the line between spectrum ends for nonspectrals. However, this line has <0.003 lm/W according to CIE colorimetric data and is therefore effectively invisible. It only represents the limit of theoretically attainable colors, and is of no practical use in color reproduction or color appearance. Required is a locus giving optimal rather than invisible nonspectral stimuli. The problem is partly semantic. CIE wisely adopted the term colorimetric purity, rather than the original spectral luminance purity, to permit an equivalent metric for spectrals and nonspectrals, but the parameter of equivalence was never clear. Since 1 pc denotes optimal aperture‐color stimuli for spectrals, arguably 1 pc should denote optimal stimuli consistently for all stimuli. The problem reduces to calculating optimal aperture‐color stimuli (“optimal” in energy efficiency in color‐matching) for nonspectrals, shown to comprise 442 + 613 nm in all CIE illuminants. This remedy merely requires redefinition of 1 pc for nonspectrals as the line 442–613 nm, and gives meaningful pc values over the hue cycle allowing new research of chromatic luminance relations with color appearance. © 2007 Wiley Periodicals, Inc. Col Res Appl, 32, 469–476, 2007 相似文献