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Improvement of the exemplar-based inpainting

机译:基于样例的修补的改进

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This paper proposes an improved exemplar-based inpainting using image segmentation, image quilting, and spatial blending to reduce the excessively propagating texture and pathological geometric configurations. A graph-based segmentation is used to generate an initial segmented map. The segmented regions are merged by a K-means approach with texture similarity to generate a further texture-based segmented map, which reduces the candidate source space and determines whether to utilize image quilting in the iterative updating process. An improved spatial blending is introduced as a postprocess to smooth the filled image when the filling process is completed. Experimental results show that this exemplar-based inpainting approach has a good visual effect and reduces the computing time. (C) 2016 SPIE and IS&T
机译:本文提出了一种改进的基于样例的图像修补,它使用图像分割,图像缝和空间融合来减少过度传播的纹理和病理性几何构造。基于图的分割用于生成初始分割图。分割的区域通过具有纹理相似性的K-means方法合并以生成进一步的基于纹理的分割图,从而减少了候选源空间并确定是否在迭代更新过程中使用图像quil缝。引入了一种改进的空间融合作为后期处理,以在填充过程完成时使填充的图像平滑。实验结果表明,这种基于样例的修复方法具有良好的视觉效果,减少了计算时间。 (C)2016 SPIE和IS&T

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