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Subpixel Rendering Method for Color Error Minimization on Subpixel Structured Display

机译:子像素结构化显示器上的颜色误差最小化的子像素渲染方法

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This study investigates the color error problems posed by large flat panel displays and proposes a subpixel-rendering algorithm to mitigate the problem. The color error problems are caused by Mach band effect and the convergence error of a pixel on large subpixel structured displays and named a color band error. The proposed method includes three processes; a finding process of areas or pixels generating the error, an estimating process of the error, and a correction process of the error. To correct the color band error, we take an error erosion approach, an error concealment approach, and a hybrid approach of the error erosion and the error concealment. In this paper, we experimented to know the threshold where human vision can detect by a psychophysical method. In addition, we applied our proposed method to a commercial 42" plasma display to confirm the effect. The results show that all observers see the color band error at a sharp edge having above 64-gray difference and the converted test images by our algorithm are preferred to the original test images. Finally, this paper reports that the Mach band effect and the convergence error on large subpixel structured display produce color band errors on images having sharp edge and the proposed method effectively corrects the color band errors.
机译:这项研究调查了大型平板显示器带来的颜色误差问题,并提出了一种亚像素渲染算法来缓解该问题。颜色误差问题是由马赫带效应和大型子像素结构的显示器上像素的会聚误差引起的,因此被称为色带误差。所提出的方法包括三个过程。查找产生误差的区域或像素的过程,误差的估计过程以及误差的校正过程。为了校正色带误差,我们采用了误差腐蚀方法,误差隐藏方法以及误差腐蚀和误差隐藏的混合方法。在本文中,我们尝试通过心理物理方法了解人类视觉可以检测到的阈值。此外,我们将提出的方法应用于商用的42英寸等离子显示器,以确认效果。结果表明,所有观察者都看到具有大于64灰度差的锐利边缘的色带误差,并且通过我们的算法转换的测试图像为最后,本文报道了大亚像素结构显示器上的马赫带效应和会聚误差在具有锐利边缘的图像上产生了色带误差,并且该方法有效地校正了色带误差。

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