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Exemplar-based image inpainting using structural feature offsets statistics

机译:基于示例的基于图像的图像修复了使用结构特征偏移统计数据

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To well maintain structure coherence of a repaired image, an exemplar-based image inpainting algorithm using structural feature offsets statistics is proposed. First, the whole degraded image is partitioned into structural part and non-structural part using Canny operator. Afterwards, the patch offsets statistics of each part are separately calculated and only a few dominant offsets for each part are selected as candidate labels. Finally, global energy function is constructed by simultaneously considering color and gradient information and solved by using multi-label graph cuts. Experimental results show that the proposed method yields generally better inpainted effect than three state-of-the-art methods in terms of structure coherence and neighborhood consistence.
机译:为了良好地维持修复图像的结构相干性,提出了一种使用结构特征偏移统计数据的示例性的基于图像的图像初始化算法。首先,使用罐内操作员将整个降级的图像分成结构部件和非结构部件。然后,分别计算每个部分的补丁偏移统计,并且仅选择每个部分的少数主导偏移作为候选标签。最后,通过同时考虑颜色和梯度信息来构造全局能量功能,并通过使用多标签图纸来解决。实验结果表明,在结构一致性和邻域一致方面,该方法通常比三种最新方法产生更好的染色效果。

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