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Spatial Intensity Channel Replacement Daltonization (SIChaRDa)

机译:空间强度通道替换道尔顿化(SIChaRDa)

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Color-deficient observers are often confronted with problems in daily life due to the fact that some colors appear less differentiable than for normal sighted people. So-called daltonization methods have been proposed to increase color contrast for color-deficient people. We propose two methods for better daltonization solutions by Spatial Intensity Channel Replacement Daltonization (SIChaRDa). We propose replacing the intensity channel with a grayscale version of the image computed by using spatial color-to-gray methods that are either capable of translating color contrasts into lightness contrasts or that are capable of translating color edges into lightness edges, and/or integrating information from the red-green channel into the intensity channel. We tested two implementations on different types of images, and we could show that results depend on the one hand on the algorithm used for computing the grayscale image, and on the other hand on the content of the image. We show that the spatial methods work best on real-life images were confusing colors are directly adjacent to each other, respectively where they are in close proximity. On the contrary, using composed artificial images with borders of white space between colors - like for example in the Ishihara plates - leads only to unsatisfactory results.
机译:缺乏颜色的观察者在日常生活中经常会遇到一些问题,原因是某些颜色看起来比正常人的分辨力差。已经提出了所谓的道尔顿化方法来增加色差人的颜色对比度。我们提出了两种通过空间强度通道替换道尔顿(SIChaRDa)获得更好道尔顿解决方案的方法。我们建议将强度通道替换为通过使用空间颜色到灰色方法计算的图像的灰度版本,该方法可以将颜色对比度转换为亮度对比度,或者可以将颜色边缘转换为亮度边缘和/或积分信息从红绿色通道进入强度通道。我们在不同类型的图像上测试了两种实现,我们可以证明结果一方面取决于用于计算灰度图像的算法,另一方面取决于图像的内容。我们表明,空间方法在现实生活的图像上效果最佳,因为令人困惑的颜色是彼此直接相邻的,或者它们彼此紧邻的颜色。相反,使用合成的人造图像在颜色之间具有白色边界的情况下(例如在Ishihara印版中)只会导致效果不理想。

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