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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的误差扩散方法,该方法可以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可识别的结构。我们的方法在概念上简单且计算效率高。分析源图像,并检测其本地频率内容。频率内容的主要成分(主频率,方向和对比度)用作查找表索引,用于预先计算的标准误差扩散修正数据库。修改包括阈值调制和误差扩散系数的变化。整个系统的校准方式应使生成的半色调图像在视觉上接近原始图像(恒定强度的色块,包含不同频率/方向/对比度的正弦波的色块以及不同来源的自然图像)。我们的系统所产生的视觉质量图像可与[Pang等,2003年。 2008],但速度要快得多。当处理几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 et al。 2008]。由于它的速度与高视觉质量相结合,我们的错误扩散算法可用于许多可能需要数字半色调的实际应用中:打印,可视化,几何处理,各种采样技术等。

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