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Subpixel Rendering Method for Color Error Minimization on Subpixel Structured Display

机译:子像素结构显示屏上的颜色误差最小化子像素渲染方法

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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:本研究调查了大型平板显示器构成的颜色误差问题,并提出了一种缓解问题的子像素渲染算法。颜色误差问题是由Mach频段效应和大型子像素结构显示器上的像素的收敛误差引起的,并命名色带误差。该方法包括三个过程;生成误差的区域或像素的发现过程,误差的估计过程以及误差的校正处理。要纠正色带错误,我们采取错误侵蚀方法,错误隐藏方法,以及错误侵蚀的混合方法和错误隐藏。在本文中,我们尝试了解人类视力可以通过心理物理方法检测的阈值。此外,我们将所提出的方法应用于商业42“等离子显示器以确认效果。结果表明,所有观察者都在具有高于64灰度差异的尖锐边缘处看到色带误差,并且通过我们的算法转换后的测试图像是优选的是原始测试图像。最后,本文报告说,Mach频段效应和大型子像素结构显示器上的收敛误差在具有尖锐边缘的图像上产生色带误差,并且所提出的方法有效地校正色带误差。

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