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	A patch-based low-rank tensor approximation model for multiframe image denoising (EI收录)
	Hao, Ruru[1]; Su, Zhixun[1]
刊名	Journal of Computational and Applied Mathematics
	2018
卷号	329页码:125-133
关键词	Computerized tomography Constrained optimization Iterative methods Lagrange multipliers Magnetic resonance imaging Matrix algebra Optimization Spectroscopy Tensors
URL标识	查看原文
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/2169658
专题	华南理工大学
作者单位	[1] School of Mathematical Sciences, Dalian University of Technology, China
推荐引用方式 GB/T 7714	Hao, Ruru[1],Su, Zhixun[1]. A patch-based low-rank tensor approximation model for multiframe image denoising (EI收录)[J]. Journal of Computational and Applied Mathematics,2018,329:125-133.
APA	Hao, Ruru[1],&Su, Zhixun[1].(2018).A patch-based low-rank tensor approximation model for multiframe image denoising (EI收录).Journal of Computational and Applied Mathematics,329,125-133.
MLA	Hao, Ruru[1],et al."A patch-based low-rank tensor approximation model for multiframe image denoising (EI收录)".Journal of Computational and Applied Mathematics 329(2018):125-133.

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