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Layer-based image completion by poisson surface reconstruction

机译:泊松曲面重构实现基于图层的图像完成

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Image completion has been widely used to repair damaged regions of a given digital image in a visually plausible way. However, it is difficult to infer appropriate information, meanwhile keep globally coherent just from the origin image when its critical parts are missing. To address this problem, we propose a novel layer-divided image completion scheme, which contains two major steps. First, we extract foregrounds of both target image and source image, and then we apply a guided Poisson surface reconstruction technique to complete the target foreground according to parameters obtained from optimal-matching calculation. Second, to fill the remaining damaged part, a related exemplar-based image completion algorithm is further devised. Several experiments and comparisons show the effectiveness and robustness of our proposed algorithm.
机译:图像完成已广泛用于以视觉上合理的方式修复给定数字图像的损坏区域。但是,很难推断出适当的信息,同时仅在缺少原始图像的关键部分时才从原始图像保持全局一致。为了解决这个问题,我们提出了一种新颖的分层图像完成方案,该方案包含两个主要步骤。首先,我们提取目标图像和源图像的前景,然后根据最佳匹配计算获得的参数,应用引导的泊松表面重构技术完成目标前景。其次,为了填充剩余的受损部分,进一步设计了相关的基于示例的图像完成算法。若干实验和比较显示了我们提出的算法的有效性和鲁棒性。

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