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首页> 外文期刊>Journal of the Society for Information Display >Hue rotation (HR) and hue blending (HB): Real-time image enhancement methods for digital component video signals to support red-green color-defective observers
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Hue rotation (HR) and hue blending (HB): Real-time image enhancement methods for digital component video signals to support red-green color-defective observers

机译：色相旋转（HR）和色相融合（HB）：用于数字分量视频信号的实时图像增强方法，以支持有红绿色缺陷的观察者

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摘要

The mutual understanding of color-normal observers (CNOs) and color-defective observers (CDOs) is now essential because personal color information display environments have been widely adopted. However, existing tools for CDOs offer only color discrimination; they fail to support color impression (ie, saturation and contrast). Therefore, we need a novel tool that offers help in distinguishing opponent colors, while preserving color saturation. We introduce two key techniques for realizing this difficult goal. The former is the repeated sequential display of the original and processed images to support the formation of unified correct percepts that provide discrimination of both red-green and yellow-blue opponent colors. One image, ie, original, exhibits correct yellow-blue but distorted red-green information for CDOs while the other, ie, processed, provides synthesized distinguishable red-green but confusable yellow-blue information for CDOs; here, hue rotation (HR) is useful for advanced users whereas hue blending (HB) is suitable for general. The latter is realized by the real-time video processing available on smartphones; our algorithms support direct processing of the digital component video signal formats (eg, Y, C-R, and C-B). Subjective tests suggest that the two above-mentioned algorithms will, along with embedding a lightweight real-time dichromatic simulation facility for CNOs, greatly help the mutual understanding of CNOs and CDOs.
机译：现在，对色彩正常观察者（CNO）和色彩缺陷观察者（CDO）的相互理解至关重要，因为个人色彩信息显示环境已被广泛采用。但是，现有的CDO工具仅提供颜色辨别功能。它们无法支持色彩印象（即饱和度和对比度）。因此，我们需要一种新颖的工具，该工具可帮助您区分对手的颜色，同时保留颜色饱和度。我们介绍了实现这一困难目标的两种关键技术。前者是原始图像和已处理图像的重复顺序显示，以支持形成统一的正确感知，从而可以区分红色，绿色和黄色蓝色的对手色。一个图像，即原始图像，对于CDO具有正确的黄蓝色但失真的红绿色信息，而另一图像（即经过处理）可以为CDO提供合成的可区分的红绿色但令人困惑的黄蓝色信息。这里，色相旋转（HR）对高级用户有用，而色相混合（HB）适合一般用户。后者是通过智能手机上的实时视频处理来实现的；我们的算法支持直接处理数字分量视频信号格式（例如Y，C-R和C-B）。主观测试表明，上述两种算法，以及为CNO嵌入轻量级实时双色仿真工具，将大大有助于CNO和CDO的相互理解。

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