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Dither matrix estimation based on pixel histograms of halftones

机译：基于半色调像素直方图的抖动矩阵估计

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Highlights•A pixel-histogram based approach for estimating the dither matrix is proposed.•The dithering at a site is regarded as a testing of getting a black halftone pixel.•The components of dither matrix are recovered by sorting the pixel histograms.•The proposed approach can take advantage of the whole halftone data.•The proposed approach is computationally simple.AbstractA dithering halftone is typically binary and generated by comparing the continuous-tone levels with periodic thresholds, which are two-dimensional repetition of a basic threshold matrix called the dither matrix. In many applications it is required to estimate the thresholds (that is, the period and the dither matrix) for a halftone. The period can be estimated conventionally by examining the autocorrelation functions or Fourier spectra. This paper focuses on the estimation of the dither matrix. In this paper, we regard the dithering at every site as a testing of getting a black halftone pixel and then estimate the dither matrix based on the pixel histograms of the halftone. Such a pixel-histogram based approach (PHA) is in contrast to the conventional full-dot-pattern based approach (FDPA), which is based on block histograms. The use of pixel histograms provides better efficiency: the usage of more information (on the whole rather than partial image data), the stronger resistance to the damage caused by the size increasing of dither, and the simpler computation. The experimental results show that compared with the FDPA, our PHA has higher percentages of successful estimates, is less damaged by the increase of dither size, and is computationally simpler.
机译： 突出显示 • 提出了一种基于像素直方图的抖动矩阵估计方法。 • 在站点上的抖动被视为对黑色半色调像素的测试。 • 通过对像素直方图进行排序来恢复抖动矩阵的分量。 • 建议的方法可以利用整个半色调数据。 • 建议的方法在计算上很简单。 摘要 < ce：abstract-sec id =“ abss0002” view =“ all”> 抖动半色调通常是二进制的，通过将连续色调的电平与周期进行比较来生成阈值，这是称为抖动矩阵的基本阈值矩阵的二维重复。在许多应用中，需要估计半色调的阈值（即周期和抖动矩阵）。通常可以通过检查自相关函数或傅立叶谱来估算周期。本文着重于抖动矩阵的估计。在本文中，我们将每个位置的抖动视为获取黑色半色调像素的测试，然后根据半色调的像素直方图估算抖动矩阵。这种基于像素直方图的方法（PHA）与基于块直方图的常规基于全点图案的方法（FDPA）相反。像素直方图的使用提供了更好的效率：使用更多的信息（整体而不是部分图像数据），对抖动大小增加导致的损坏具有更强的抵抗力，并且计算更简单。实验结果表明，与FDPA相比，我们的PHA成功估计的百分比更高，抖动大小的增加所造成的损害更少，并且计算更简单。

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