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Guest session — Image processing invited paper: A Cauchy problem for an inverse problem in image inpainting

机译:来宾会议—图像处理邀请论文:图像修补中反问题的柯西问题

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Image inpainting consists of reconstructing lost or deteriorated parts of an image. Different techniques can be applied to solve this problem. In particular, partial differential equations (PDEs) are widely used and are proved to be efficient. If we denote by Ω the entire image domain, the image inpainting problem is then to fill in image information in the incomplete/damaged region D ⊂ Ω based on the image information available out side D, i.e., in ΩD. When this information is available in a neighborhood of the whole boundary ∂D, it can be used as a Dirichlet boundary condition for the partial differential equation that propagates the information inside D. The aim of this work is to treat the case when this information is not available near a part of the boundary ∂D. Image inpainting in this case is considered as a linear Cauchy problem for the harmonic inpainting, and a nonlinear Cauchy problem for images containing edges. The novelty of this work has two folds. The first consists in extending the work introduced for a nonlinear elliptic equation. The Cauchy problem is formulated as a two-player Nash game. The first player is given the known Dirichlet data and uses the Neumann condition prescribed over the inaccessible part of the boundary as strategy variable. The second player is given the known Neumann data, and plays with the Dirichlet condition prescribed over the inaccessible boundary. The two players solve in parallel the associated Boundary Value Problems. In the second step, the proposed approach is exploited in image inpaiting. The image information in the incomplete/damaged region is completed by the corresponding Cauchy solution. Some numerical experiments are provided to illustrate the efficiency and stability of our algorithm for several image inpainting examples.
机译:图像修补包括重建图像的丢失或损坏的部分。可以应用不同的技术来解决此问题。特别地,偏微分方程(PDE)被广泛使用并被证明是有效的。如果我们用Ω表示整个图像域,那么图像修补问题就是基于D侧可用的图像信息(即ΩD)在不完整/损坏区域DΩ中填充图像信息。当此信息在整个边界∂D的邻域中可用时,可以用作在D内传播信息的偏微分方程的Dirichlet边界条件。这项工作的目的是在以下情况下处理该信息:在边界∂D的一部分附近不可用。在这种情况下,图像修补被认为是谐波修补的线性柯西问题,而对于包含边缘的图像则被视为非线性柯西问题。这项工作的新颖性有两个方面。首先是扩展为非线性椭圆方程引入的工作。柯西问题被表述为两人纳什游戏。首先为玩家提供已知的Dirichlet数据,并使用边界不可访问部分规定的诺伊曼条件作为策略变量。第二名玩家将获得已知的诺伊曼数据,并在不可访问的边界上规定的Dirichlet条件下玩牌。两家公司并行解决了相关的边值问题。在第二步中,将所提出的方法用于图像缺失。不完整/损坏区域中的图像信息由相应的柯西解决方案完成。提供了一些数值实验来说明我们的算法在几个图像修复实例中的有效性和稳定性。

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