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	STRUCTURE-GUIDED IMAGE COMPLETION VIA REGULARITY STATISTICS
	Yang, Shuai ; Liu, Jiaying ; Song, Sijie ; Li, Mading ; Guo, Zongming
	2016
关键词	Image completion structure detection perspective transformation image inpainting
英文摘要	In this paper, we propose a novel hierarchical image completion approach using regularity statistics, considering structure features. Guided by dominant structures, the target image is used to generate reference images in a self-reproductive way by image data enhancement. The structure-guided image data enhancement allows us to expand the search space for samples. A Markov Random Field model is used to guide the enhanced image data combination to globally reconstruct the target image. For lower computational complexity and more accurate structure estimation, a hierarchical process is implemented. Experiments demonstrate the effectiveness of our method comparing to several state-of-the-art image completion techniques.; CPCI-S(ISTP); 1711-1715
语种	英语
出处	IEEE International Conference on Acoustics, Speech, and Signal Processing
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/459992]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Yang, Shuai,Liu, Jiaying,Song, Sijie,et al. STRUCTURE-GUIDED IMAGE COMPLETION VIA REGULARITY STATISTICS. 2016-01-01.

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