Metamer density estimated color correction
Metamer density estimated color correction
复制标题
等色异构体密度估计颜色校正
DOI：
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发表时间：
2009
期刊：
影响因子：
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通讯作者：
R. Grigat
中科院分区：
文献类型：
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作者：
P. Urban;R. Grigat
色彩校正是将扫描仪或数码相机的响应值转换为与设备无关的色彩空间。一般来说，由于不同的采集和观看光源以及大多数设备不满足路德-艾夫斯条件，这种转换并不是唯一的。在本文中，我们提出了一种在最小平均误差的意义上近似最佳色彩校正的方法。该方法基于具有代表性的反射光谱集，该集用于计算每个传感器响应的特殊基本器件元谱黑色集合和适当的基本元谱。将基元集和基元集结合在一起，可以得到一组遵循基元集集反射率密度分布的反射率。仅将集合的正光谱和有界光谱转换为观测者感知上均匀的颜色空间，得到的点云遵循采集系统和人类观测者的元集不匹配空间内设备元集的密度分布。选择这个集合的平均值进行颜色校正，因为这个点与云中所有其他点的平均颜色距离最小。我们提出了各种模拟实验的结果，考虑不同的采集和观看光源，传感器类型，噪声水平和现有的方法进行比较。
Color correction is the transformation of response values of scanners or digital cameras into a device- independent color space. In general, the transformation is not unique due to different acquisition and viewing illuminants and non-satisfaction of the Luther–Ives condition by a majority of devices. In this paper we propose a method that approximates the optimal color correction in the sense of a minimal mean error. The method is based on a representative set of reflectance spectra that is used to calculate a special basic collection of device metameric blacks and an appropriate fundamental metamer for each sensor response. Combining the fundamental metamer and the basic collection results in a set of reflectances that follows the density distribution of metameric reflectances if calculated by Bayesian inference. Transforming only positive and bounded spectra of the set into an observer’s perceptually uniform color space results in a point cloud that follows the density distribution of device metamers within the metamer mismatch space of acqcuisition system and human observer. The mean value of this set is selected for color correction, since this is the point with a minimal mean color distance to all other points in the cloud. We present the results of various simulation experiments considering different acquisition and viewing illuminants, sensor types, noise levels, and existing methods for comparison.