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An image inpainting technique based on illumination variation and structure consistency

机译:基于光照变化和结构一致性的图像修复技术

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Image inpainting is that restores the damaged region of interest by user specified or removes areas in an image. For the purpose of patching up automatically, filling in large-sized damaged areas in the image, and lowering down the operation complexity, we design an exemplar-based image inpainting as our main framework. In order to keep the structure consistency between the damaged areas and the non-damaged areas, we redefine two factors, confidence and variation, which use to determine the priority of the filling order of target (damaged) regions. With these two newly defined factors, we propose a dynamic rule to choose the best target region and the suitable patch size in each filling step. To solve the challenging problem of repairing structure in image completion, we introduce a novel image completion approach based on automatic salient structure propagation. Experimental results demonstrate that this approach can make an effective inpainting and visual quality.
机译:图像修复是根据用户指定的位置恢复损坏的感兴趣区域或删除图像中的区域。为了自动修补,填充图像中较大的损坏区域并降低操作复杂性,我们设计了基于示例的图像修复作为主要框架。为了保持受损区域和非受损区域之间的结构一致性,我们重新定义了两个因素,即置信度和变异度,这两个因素用于确定目标(受损)区域的填充顺序的优先级。有了这两个新定义的因素,我们提出了一个动态规则,以在每个填充步骤中选择最佳目标区域和合适的贴片尺寸。为了解决图像完成中修复结构的挑战性问题,我们引入了一种基于自动显着结构传播的新颖图像完成方法。实验结果表明,该方法可以实现有效的修复效果和视觉效果。

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