Coherence-enhancing line drawing for color images

被引:0
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作者
ShanDong Wang
ZiYang Ma
XueHui Liu
YanYun Chen
EnHua Wu
机构
[1] Chinese Academy of Sciences,State Key Laboratory of Computer Science, Institute of Software
[2] University of Macau,Department of Computer and Information Science
[3] Graduate University of Chinese Academy of Sciences,undefined
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关键词
non-photorealistic rendering; line drawing; FDoG filter; coherence-enhancing; real-time computation;
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学科分类号
摘要
Line drawing plays an important role in many image-based non-photorealistic applications. However, most existing approaches use a grayscale edge detector for line extraction, so that only luminance differences between nearby image pixels is taken into account, but the chrominance differences is ignored. This leads to the undesirable consequence that visually significant edges in adjacent regions with different colors of similar luminance cannot be detected. To address this limitation, we present a novel enhanced line drawing method based on a flow-based difference-of-Gaussians (FDoG) filter. Because of an inherent property of the thresholded DoG edge model, captured lines may appear dislodged from the true edges in the image. To this end, we provide a gradient-guided warping technique so that smooth and coherent lines can be extracted in the correct location. The GPU implementation of the proposed algorithms allows real-time performance, and experimental examples with various color images demonstrate the method’s superior qualitative performance over previous approaches.
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页码:1 / 11
页数:10
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