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Impact of HVS Models on Model-based Halftoning

机译:HVS模型对基于模型的半色调的影响

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摘要

A model for the human visual system (HVS) is an important component of many halftoning algorithms. Using the iterative direct binary search (DBS) algorithm, we compare the halftone texture quality provided by four different HVS models that have been reported in the literature. Choosing one HVS model as the best for DBS, we then develop an approximation to that model which significantly improves computational performance while minimally increasing the complexity of the code. By varying the parameters of this model, we find that it is possible to tune it to the gray level being rendered, and to thus yield superior halftone quality across the tone scale. We then develop a dual-metric DBS algorithm that effectively provides a tone-dependent HVS model without a large increase in computational complexity.
机译:人类视觉系统(HVS)的模型是许多半色调算法的重要组成部分。使用迭代直接二进制搜索(DBS)算法,我们比较了文献中已报道的四种不同HVS模型提供的半色调纹理质量。选择一种最适合DBS的HVS模型,然后我们对该模型进行近似,从而可以显着提高计算性能,同时将代码的复杂性降至最低。通过更改此模型的参数,我们发现可以将其调整到要渲染的灰度级,从而在整个色调范围内产生出色的半色调质量。然后,我们开发了一种双度量DBS算法,该算法可有效地提供依赖于色调的HVS模型,而不会大幅增加计算复杂性。

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