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	Adaptive Local Nonparametric Regression for Fast Single Image Super-Resolution
	Zhang, Yulun ; Zhang, Yongbing ; Zhang, Jian ; Wang, Haogian ; Wang, Xingzheng ; Dai, Qionghai
	2015
关键词	Adaptive local linear regression dictionary learning mutual coherence projection matrix super-resolution QUALITY
英文摘要	We propose a fast single image super-resolution algorithm based on adaptive local nonparametric regression. Making use of dictionary learning and regression, we learn multiple projection matrices mapping low-resolution features to their corresponding high-resolution ones directly. Different from previous linear regression that needs some constant parameters, our method would not use extra parameters for regression. We use the mutual coherence between dictionary atom and low-resolution feature as a label to reconstruct more sophisticated high-resolution feature. As we use the same form of mutual coherence as labels in both training and testing phases, our method would lead to an adaptive local linear regression model. Moreover, we investigate the statistical property of the dictionary atoms from the training features. Utilizing the learned statistical priors, our method would not only obtain more useful dictionary atoms, but also further decrease the computational time. As shown in our experimental results, the proposed method yields high-quality super-resolution images quantitatively and visually against state-of-the-art methods.; National High-tech R&D Program of China (863 Program) [2015AA015901]; National Natural Science Foundation of China [61170195, U1201255, U1301257]; Guangdong Natural Science Foundation [2014A030313751]; CPCI-S(ISTP)
语种	英语
出处	IEEE Visual Communications and Image Processing (VCIP) Conference
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/470300]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Zhang, Yulun,Zhang, Yongbing,Zhang, Jian,et al. Adaptive Local Nonparametric Regression for Fast Single Image Super-Resolution. 2015-01-01.

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