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Exemplar-based Image Inpainting Using Structural Feature Offsets Statistics

机译:使用结构特征偏移量统计的基于示例的图像修复

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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:为了很好地保持修复图像的结构一致性,提出了一种基于样本的利用结构特征偏移量统计的图像修复算法。首先,使用Canny算子将整个退化图像分为结构部分和非结构部分。之后,分别计算每个部分的补丁偏移统计信息,并且仅选择每个部分的少数主要偏移作为候选标签。最后,通过同时考虑颜色和渐变信息来构造全局能量函数,并通过使用多标签图割来求解。实验结果表明,在结构相干性和邻域一致性方面,所提出的方法通常比三种最新方法产生更好的修复效果。

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