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The color gamut of LCD and its analytical expression

机译:LCD的色域及其分析表达

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In cross-media color image reproduction, gamut mapping is needed due to gamut difference among different media. The first step of gamut mapping should be the determination of gamut boundaries of each medium involved, no matter what kind of mapping algorithm is to be used. It may be expected that an analytical expression for a boundary is preferable to a set of discrete data, since it would make the determination of the intersection point between a boundary and a "mapping line" easier and faster. This paper describes LCD display gamut boundary surfaces with a form of Zernike polynomial. In CIE1976L*a*b* color space, each color point on the boundary can be expressed as L*=L*(a*,b*) and every boundary can be expanded into a series of Zernike polynomials with appropriate coefficients. These coefficients can be obtained with sufficient experiment data of boundary points and existing algorithms. Experiments have been executed for a LCD display with(R,G,B) as its input. The 6 boundaries in RGB space would be formed respectively by (0,G,B),(R,0,B),(R,G,0),(255,G,B),(R,255,B) and (R,G,255) where each of R,G,B varies from 0 to 255. Then 6 corresponding sets of Zernike coefficients are calculated, based on about half of the measured L*a*b*'s for each boundary. A comparison between original measured data and the data predicted by Zernike polynomials shows that, not only for the data that have been used to calculate the coefficients, but also for those not used, the differences are acceptably small even negligible with only a few exceptions.
机译:在跨媒体彩色图像再现中,由于不同媒体之间的色域差异,需要域映射。无论要使用什么样的映射算法,都应该确定所涉及的每个介质的曲面边界的第一步。可以预期,边界的分析表达式是优选的一组离散数据,因为它会使边界和“映射线”之间的交叉点确定更容易和更快。本文介绍了具有Zernike多项式形式的LCD显示色域边界表面。在CIE1976L * A * B *颜色空间中,边界上的每个颜色点可以表示为L * = L *(A *,B *),并且每个边界可以扩展到具有适当系数的一系列Zernike多项式中。可以利用边界点和现有算法的充分实验数据获得这些系数。已经执行了使用(R,G,B)作为其输入的LCD显示器的实验。 RGB空间中的6个边界分别由(0,g,b),(r,0,b),(r,g,0),(255,g,b),(r,255,b)形成(R,G,255),其中R,G,B中的每一个都从0到255变化。然后,基于每个边界的测量的L * A * B *的约一半,计算6个相应的Zernike系数。原始测量数据与Zernike多项式预测的数据之间的比较显示,不仅用于计算系数的数据,而且对于那些未使用的数据,甚至可以忽略几个例外,差异甚至可以忽略不计。

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