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Image Completion Using Sample Synthesis

机译:使用样本合成完成图像

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摘要

The issue of image completion is well developed in these years. Most of them reconstruct damaged area by referring to the under-repaired images themselves. However, they may fail if damaged portion collapse their structure which is unique and important. We propose to use an external reference image to repair the damaged image and the method provides the following three contributions: (1) an algorithm of fast contour matching is proposed to repair damaged images by referring to external sample images. Critical structural information can be rebuilt which is missing in original damaged area. (2) An algorithm of fragment color transform is proposed to resolve the problem of creating false transform to non-existent color if traditional histogram specification were used. (3) An algorithm of K map threshold weighted synthesis is proposed to resolve the problem of creating false textures caused by non-existence of similar block in original damaged area. Several experiments are executed and the results clearly indicate that defects mentioned above are able to fix more efficiently. Especially, the present method shows good performance for texture accommodation in the joint area. Therefore, it is ideal for the task of completing images with unique structure missing in the damaged area.
机译:近年来,图像完成的问题已经很好地发展了。他们中的大多数人通过参考未充分修复的图像来重建受损区域。但是,如果损坏的部分破坏其结构,这可能是失败的,这是独特而重要的。我们提议使用外部参考图像来修复受损图像,该方法提供以下三个贡献:(1)提出了一种快速轮廓匹配算法,其通过参考外部样本图像来修复受损图像。可以重建原始损坏区域中缺少的重要结构信息。 (2)提出了一种分片颜色变换算法,解决了使用传统直方图规范时将假变换转化为不存在颜色的问题。 (3)提出了一种K图阈值加权综合算法,以解决由于原始损坏区域中不存在类似块而造成虚假纹理的问题。执行了几次实验,结果清楚地表明,上述缺陷可以更有效地修复。特别地,本方法显示出在关节区域中的纹理调节的良好性能。因此,它是完成损坏区域中缺少独特结构图像的任务的理想选择。

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