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A Tensor-based Technique for Structure-aware Image Inpainting

机译:一种基于张解的结构感知图像修复技术

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Image inpainting is an active area of study in computer graphics, computer vision and image processing. Different image inpainting algorithms have been recently proposed. Most of them have shown their efficiency with different image types. However, failure cases still exist, especially when dealing with local image variations. This paper presents an image inpainting approach based on structure layer modeling, where this latter is represented by the second-moment matrix, also known as the structure tensor. The structure layer of the image is first inpainted using the non-parametric synthesis algorithm of Wei and Levoy, then the inpainted field of second-moment matrices is used to constrain the inpainting of the image itself. Results show that using the structural information, relevant local patterns can be better inpainted comparing to the standard intensity-based approach.
机译:图像批量是计算机图形,计算机视觉和图像处理中的一个活跃的研究领域。最近已经提出了不同的图像修复算法。其中大多数都以不同的图像类型显示了它们的效率。然而,故障情况仍然存在,特别是在处理局部图像变化时。本文介绍了基于结构层建模的图像初始化方法,其中后者由第二矩矩阵表示,也称为结构张量。使用Wei和Levoy的非参数综合算法首先染色图像的结构层,然后使用第二矩矩阵的预测字段来限制图像本身的预测。结果表明,使用结构信息,与基于标准强度的方法相比,可以更好地验收相关的本地模式。

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