Contour stencils for edge-adaptive image interpolation
Contour stencils for edge-adaptive image interpolation
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DOI：
10.1117/12.806014
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发表时间：
2009-01
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通讯作者：
Pascal Getreuer
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文献类型：
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作者：
Pascal Getreuer
我们首先开发一个简单的方法来检测图像轮廓的局部方向，然后使用此检测设计一个边缘自适应图像插值策略。检测基于总变化：沿候选曲线的小的总变化沿着意味着图像沿该曲线近似沿着恒定，这表明它是轮廓的良好近似。所提出的策略是测量“轮廓模板”上的总变化，“轮廓模板”是一组位于图像中小块区域上的平行曲线。该轮廓模板检测用于设计边缘自适应图像插值策略。插值是计算效率高，在各种图像特征上稳健地操作，并且在与现有方法的比较中具有竞争力。该方法很容易扩展到矢量值数据，并证明了彩色图像插值。轮廓支架的其他应用也进行了讨论。
We first develop a simple method for detecting the local orientation of image contours and then use this detection to design an edge-adaptive image interpolation strategy. The detection is based on total variation: small total variation along a candidate curve implies that the image is approximately constant along that curve, which suggests it is a good approximation to the contours. The proposed strategy is to measure the total variation over a "contour stencil," a set of parallel curves localized over a small patch in the image. This contour stencil detection is used to design an edge-adaptive image interpolation strategy. The interpolation is computationally efficient, operates robustly over a variety of image features, and performs competitively in a comparison against existing methods. The method extends readily to vector-valued data and is demonstrated for color image interpolation. Other applications of contour stencils are also discussed.