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Structure-aware error diffusion

机译:结构感知错误扩散

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We present an original error-diffusion method which produces visually pleasant halftone images while preserving fine details and visually identifiable structures present in the original images. Our method is conceptually simple and computationally efficient. The source image is analyzed, and its local frequency content is detected. The main component of the frequency content (main frequency, orientation and contrast) serve as lookup table indices to a pre-calculated database of modifications to a standard error diffusion. The modifications comprise threshold modulation and variation of error-diffusion coefficients. The whole system is calibrated in such a way that the produced halftone images are visually close to the original images (patches of constant intensity, patches containing sinusoidal waves of different frequencies/orientations/contrasts, as well as natural images of different origins). Our system produces images of visual quality comparable to that presented in [Pang et al. 2008], but much faster. When processing typical images of linear size of several hundreds of pixels, our error-diffusion system is two to three orders of magnitude faster than [Pang et al. 2008]. Thanks to its speed combined with high visual quality, our error-diffusion algorithm can be used in many practical applications which may require digital halftoning: printing, visualization, geometry processing, various sampling techniques, etc.
机译:我们提出了一种原始误差扩散方法,其产生视觉上令人愉快的半色调图像,同时保留原始图像中存在的精细细节和视觉上可识别的结构。我们的方法是概念上简单且计算的高效。分析源图像,检测其局部频率内容。频率内容(主频率,方向和对比度)的主要组成部分用作查找表索引,以预先计算的修改数据库到标准误差扩散。修改包括阈值调制和误差扩散系数的变化。整个系统以这样的方式校准,即产生的半色调图像在视觉上接近原始图像(恒定强度的块,包含不同频率/取向/对比度的正弦波的贴片,以及不同起源的自然图像)。我们的系统产生了与[Pang等人。 2008],但要快得多。当处理数百个像素的线性尺寸的典型图像时,我们的误差扩散系统比[Pang等人更快。 2008]。由于其速度结合了高视觉质量,因此我们的误差扩散算法可用于许多可能需要数字半色调的实际应用:打印,可视化,几何处理,各种采样技术等。

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