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Pixel and Patch Reordering for Fast Patch Selection in Exemplar-Based Image Inpainting

机译:基于样例的图像修复中像素和补丁的重新排序以快速选择补丁

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This letter presents a scheme to improve the running time of exemplar-based image inpainting, first proposed by Criminisi et al. In the exemplar-based image inpainting, a patch that contains unknown pixels is compared to all the patches in the known region in order to find the best match. This is very time-consuming and hinders the practicality of Criminisi's method to be used in real time. We show that a simple bounding algorithm can significantly reduce number of distance calculations, and thus the running time. Performance of the bounding algorithm is affected by the order of patches that are compared, as well as the order of pixels in a patch. We present pixel and patch ordering schemes that improve the performance of bounding algorithms. Experiments with well-known images used in inpainting literature show that the proposed reordering scheme can reduce running time of the bounding algorithm up to 50%.
机译:这封信提出了一种方案,该方案由Criminisi等人首先提出,旨在改善基于示例的图像修复的运行时间。在基于示例的图像修复中,将包含未知像素的补丁与已知区域中的所有补丁进行比较,以找到最佳匹配。这非常耗时,并且妨碍了实时使用Criminisi方法的实用性。我们证明了一种简单的边界算法可以显着减少距离计算的次数,从而减少运行时间。边界算法的性能受比较的补丁顺序以及补丁中像素顺序的影响。我们提出了像素和补丁排序方案,以改善边界算法的性能。在修复文献中使用知名图像进行的实验表明,提出的重排序方案可以将边界算法的运行时间减少多达50%。

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