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Exemplar-Based Image Inpainting Using Multiscale Graph Cuts

机译:使用多尺度图割的基于示例的图像修复

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We present a novel formulation of exemplar-based inpainting as a global energy optimization problem, written in terms of the offset map. The proposed energy function combines a data attachment term that ensures the continuity of reconstruction at the boundary of the inpainting domain with a smoothness term that ensures a visually coherent reconstruction inside the hole. This formulation is adapted to obtain a global minimum using the graph cuts algorithm. To reduce the computational complexity, we propose an efficient multiscale graph cuts algorithm. To compensate the loss of information at low resolution levels, we use a feature representation computed at the original image resolution. This permits alleviation of the ambiguity induced by comparing only color information when the image is represented at low resolution levels. Our experiments show how well the proposed algorithm performs compared with other recent algorithms.
机译:我们提出了一种基于示例性修补的新公式,将其作为全球能源优化问题,以偏移图的形式编写。所提出的能量函数将确保附着区域在边界上的重建连续性的数据附加项与确保孔内视觉上一致的重建的平滑度项结合在一起。该公式适用于使用图割算法获得全局最小值。为了降低计算复杂度,我们提出了一种有效的多尺度图割算法。为了补偿低分辨率级别的信息丢失,我们使用以原始图像分辨率计算的特征表示。当以低分辨率水平表示图像时,这允许减轻仅通过比较颜色信息而引起的歧义。我们的实验表明,与其他最新算法相比,该算法的性能如何。

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