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	Neighborhood regression for edge-preserving image super-resolution
	Li, Yanghao ; Liu, Jiaying ; Yang, Wenhan ; Guo, Zongming
	2015
英文摘要	There have been many proposed works on image super-resolution via employing different priors or external databases to enhance HR results. However, most of them do not work well on the reconstruction of high-frequency details of images, which are more sensitive for human vision system. Rather than reconstructing the whole components in the image directly, we propose a novel edge-preserving super-resolution algorithm, which reconstructs low- and high-frequency components separately. In this paper, a Neighborhood Regression method is proposed to reconstruct high-frequency details on edge maps, and low-frequency part is reconstructed by the traditional bicubic method. Then, we perform an iterative combination method to obtain the estimated high resolution result, based on an energy minimization function which contains both low-frequency consistency and high-frequency adaptation. Extensive experiments evaluate the effectiveness and performance of our algorithm. It shows that our method is competitive or even better than the state-of-art methods. ? 2015 IEEE.; EI; 1201-1205; 2015-August
语种	英语
出处	40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015
DOI标识	10.1109/ICASSP.2015.7178160
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/423729]
专题	计算机科学技术研究所
推荐引用方式 GB/T 7714	Li, Yanghao,Liu, Jiaying,Yang, Wenhan,et al. Neighborhood regression for edge-preserving image super-resolution. 2015-01-01.

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