Error Analysis for Image Inpainting
Error Analysis for Image Inpainting
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DOI：
10.1007/s10851-006-6865-7
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发表时间：
2006-11
影响因子：
2
通讯作者：
T. Chan;S. Kang
中科院分区：
文献类型：
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作者：
T. Chan;S. Kang
图像修复是指修复丢失信息的受损图像。近年来，图像修复问题的计算方法取得了许多进展[2,4,6,9,11-13,27,28]。尽管有许多有效的算法可用，但对于这些算法在什么条件下工作良好仍然缺乏理论理解。在本文中，我们朝这个方向迈出了一步。我们通过考虑不同的图像空间（例如平滑图像、分段恒定图像和特定类型的分段连续图像）来研究修复方法的误差范围。给出了数值结果来验证理论误差范围。
Image inpainting refers to restoring a damaged image with missing information. In recent years, there have been many developments on computational approaches to image inpainting problem [2, 4, 6, 9, 11–13, 27, 28]. While there are many effective algorithms available, there is still a lack of theoretical understanding on under what conditions these algorithms work well. In this paper, we take a step in this direction. We investigate an error bound for inpainting methods, by considering different image spaces such as smooth images, piecewise constant images and a particular kind of piecewise continuous images. Numerical results are presented to validate the theoretical error bounds.