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Is the Sharp Adaptation Transform more plausible than CMCCAT2000?

机译:夏普适应性比CMCCAT2000更合理吗?

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The modified Bradford chromatic adaptation transform (CMCCAT2000) is a von Kries type model of adaptation that best accounts for a variety of corresponding colour data sets. The transform works in three stages. First, XYZs arc linearly mapped to a new 'RGB' space. The RGB sensitivities are somewhat like the cones but have their sensitivity concentrated in narrower regions of the visible spectrum. In the second stage of the transform, the Red, Green and Blue responses are multiplied by three scalars to model illuminant change. Finally, RGBs are transformed back to XYZs (in order that well established formulae for colour appearance might be used). The Sharp adaptation transform (SAT), derived from theoretical arguments, is exactly the same as CMCCAT2000 except that the sharp RGB sensor sensitivities have even narrower support. Research has shown that the SAT delivers, statistically, the same performance as CMCCAT2000. In this paper we consider whether there is any reason why CMCCAT2000 or SAT might be preferable if adaptation is considered from an observers viewpoint. Our argument builds on the premise that an observer in making a corresponding colour match is matching surface reflectance. Starting with this premise the adaptation problem is clearly ill-posed: a pair of different surface reflectances might look the same under one light but different under another (this is the metamerism problem). However, we argue that an observer understands this metamerism and so seeks only to make a plausible reflectance match. Let us suppose a reflectance B viewed under a target light is chosen to match reflectance A viewed under a reference light. We say B is plausible if and only if it is possible that if B is also viewed under the reference light it is identical to A. Adopting this definition of plausibility, we found that the Sharp Adaptation Transform supports plausible adaptation but that CMCCAT2000 supports implausible adaptation.
机译:修改的Bradford彩色适配变换(CMCCAT2000)是一个von Kries型式的适应模型,最适合各种相应的颜色数据集。该变换在三个阶段工作。首先,XYZS将线性映射到新的“RGB”空间。 RGB敏感性有些类似于锥体,但它们的敏感性集中在可见光谱的较窄区域中。在变换的第二阶段,红色,绿色和蓝色响应乘以三个标量来模拟发光体变化。最后,RGB被转换回XYZ(以便可以使用良好建立的颜色外观公式)。源自理论参数的夏普适应变换(SAT)与CMCCAT2000完全相同,不同之处在于Sharp RGB传感器敏感性甚至更窄的支持。研究表明,SAT在统计上提供,统计上与CMCCAT2000相同的性能。在本文中,我们考虑如果从观察者观察点考虑自适应,那么如果考虑了CMCCAT2000或SAT的任何原因。我们的论点建立在前提下,观察者在制作相应的颜色匹配方面是匹配的表面反射率。从这个前提开始,适应问题显然不起作用:一对不同的表面反射可能在一个光线下看起来相同,但在另一个光线下方(这是元体问题)。然而,我们认为观察者理解这种元素,因此寻求仅仅制造合理的反射率匹配。让我们假设在目标光下被选择的反射率B被选择以匹配在参考光下观察的反射率A.我们说,如果也可以在参考光下观看B的情况下,我们是合理的,如果在参考灯下看出,它与a相同。采用这种合理性的定义,我们发现夏普适应变换支持合理的适应,但CMCCAT2000支持难以置信的适应。

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