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The color gamut of LCD and it's analytical expression

机译:LCD的色域及其解析表达

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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 Zemike 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,因此需要色域映射。色域映射的第一步应该是确定所涉及的每种介质的色域边界,无论使用哪种映射算法。可以预期,对于边界的分析表达式比一组离散数据更可取,因为它将使边界和“映射线”之间的交点的确定更加容易和快捷。本文以Zemike多项式形式描述了LCD显示色域的边界表面。在CIE1976L * a * b *颜色空间中,边界上的每个色点都可以表示为L〜* = L〜*(a〜*,b〜*),并且可以将每个边界扩展为适当的Zernike多项式序列系数。可以使用足够的边界点实验数据和现有算法来获得这些系数。对于以(R,G,B)作为输入的LCD显示器已经进行了实验。 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),其中每个R,G,B在0到255之间变化。然后,基于测得的L〜* a〜* b〜*的一半,计算6组对应的Zernike系数每个边界。原始测量数据与Zernike多项式预测的数据之间的比较表明,不仅对于已用于计算系数的数据,而且对于未使用的数据,差异也很小,甚至可以忽略不计,只有少数例外。

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