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	Structure-guided image completion via regularity statistics
	Yang, Shuai ; Liu, Jiaying ; Song, Sijie ; Li, Mading ; Quo, Zongming
	2016
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. ? 2016 IEEE.; EI; 1711-1715; 2016-May
语种	英语
出处	41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016
DOI标识	10.1109/ICASSP.2016.7471969
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/436165]
专题	计算机科学技术研究所
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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