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A spatial domain optimization method to generate plane dependent masks

机译:一种空间域优化方法,用于生成平面依赖面罩

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Stochastic screening technique uses a fixed threshold array to generate halftoned images. When this technique is applied to color images, an important problem is how to generate the masks for different color planes. Ideally, a set of plane dependent color masks should have the following characteristics: a) when total ink coverage is less than 100%, no dots in different colors should overlap from each other. b) for each individual mask, dot distribution should be uniform, c) no visual artifact should be visible due to the low frequency patterns. In this paper, we propose a novel color mask generation method in which the optimal dot placement is searched directly in spatial domain. The advantage of using the spatial domain approach is that we can control directly the dot uniformity during the optimization, and we can also cope with the color plane-dependency by introducing some inter-plane constraints. We will show that using this method, we can generate plane dependent color masks with the characteristics mentioned above
机译:随机筛选技术使用固定阈值阵列来生成半色调图像。当该技术应用于彩色图像时,重要问题是如何为不同的颜色平面生成掩模。理想情况下,一组平面依赖性颜色面罩应该具有以下特征:a)当总墨水覆盖范围小于100%时,不同颜色的没有点彼此重叠。 b)对于每个单独的掩模,点分布应该是均匀的,c)由于低频图案而不应该可见视觉伪像。在本文中,我们提出了一种新的色彩掩模生成方法,其中直接在空间域中搜索最佳点放置。使用空间域方法的优点是我们可以通过引入一些平面间约束来直接控制点均匀性,并且我们也可以通过引入一些平面间隔来应对颜色平面依赖性。我们将显示使用此方法,我们可以通过上述特性生成平面依赖性颜色掩模

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