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Model-based color halftoning using direct binary search

机译:使用直接二进制搜索的基于模型的颜色半色调

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In this paper, we develop a model-based color halftoning method using the direct binary search (DBS) algorithm. Our method strives to minimize the perceived error between the continuous tone original color image and the color halftone image. We exploit the differences in how the human viewers respond to luminance and chrominance information and use the total squared error in a luminance/chrominance based space as our metric. Starting with an initial halftone, we minimize this error metric using the DBS algorithm. Our method also incorporates a measurement based color printer dot interaction model to prevent the artifacts due to dot overlap and to improve color texture quality. We calibrate our halftoning algorithm to ensure accurate colorant distributions in resulting halftones. We present the color halftones which demonstrate the efficacy of our method.
机译:在本文中,我们使用直接二进制搜索(DBS)算法开发了一种基于模型的颜色半色调方法。我们的方法致力于使连续色调原始彩色图像和彩色半色调图像之间的感知误差最小。我们利用人类观众如何响应亮度和色度信息的差异,并使用基于亮度/色度的空间中的总平方误差作为度量。从初始半色调开始,我们使用DBS算法最小化此误差指标。我们的方法还结合了基于测量的彩色打印机点相互作用模型,以防止由于点重叠而导致的伪影并改善颜色纹理质量。我们校准了半色调算法,以确保最终的半色调中的着色剂分布准确。我们介绍了彩色半色调,证明了我们方法的有效性。

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