论文标题
离散Sobolev空间中的介绍：降低不确定性的结构信息
Inpainting in discrete Sobolev spaces: structural information for uncertainty reduction
论文作者
论文摘要
在本文中，使用基于示例的方法，我们研究了介绍问题，引入了新的数学功能，该功能最小化决定了重建的质量。新的功能表达式以与理论Sobolev空间中发生的方式相似的方式考虑了Fnite差异项。此外，我们引入了一个新的优先级索引，以确定点的扫描顺序为涂料，从而优先考虑选择的不确定性。实现的结果突出了通过补丁程序的重要理论相互联系的重要方面。
In this article, using an exemplar-based approach, we investigate the inpainting problem, introducing a new mathematical functional, whose minimization determines the quality of the reconstructions. The new functional expression takes into account of fnite differences terms, in a similar fashion to what happens in the theoretical Sobolev spaces. Moreover, we introduce a new priority index to determine the scanning order of the points to inpaint, prioritizing the uncertainty reduction in the choice. The achieved results highlight important theoretical-connected aspects of the inpainting by patch procedure.
