Super-resolution reconstruction of hyperspectral images via low rank tensor modeling and total variation regularization

CORC > 沈阳自动化研究所 > 中国科学院沈阳自动化研究所 > 机器人学研究室

	Super-resolution reconstruction of hyperspectral images via low rank tensor modeling and total variation regularization
	He, Shiying; Zhou, Haiwei; Wang Y(王尧); Cao, Wenfei; Han Z(韩志)
	2016
会议名称	2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016
会议日期	July 10-15, 2016
会议地点	Beijing, China
关键词	Hyperspectral images Super-resolution reconstruction nuclear norm Folded-concave penalty 3D totalvariation
页码	6962-6965
通讯作者	He, Shiying
中文摘要	In this paper, we propose a novel approach to hyperspectral image super-resolution by modeling the global spatial-and-spectral correlation and local smoothness properties over hyperspectral images. Specifically, we utilize the tensor nuclear norm and tensor folded-concave penalty functions to describe the global spatial-and-spectral correlation hidden in hyperspectral images, and 3D total variation (TV) to characterize the local spatial-and-spectral smoothness across all hyperspectral bands. Then, we develop an efficient algorithm for solving the resulting optimization problem by combing the local linear approximation (LLA) strategy and alternative direction method of multipliers (ADMM). Experimental results on one hyperspectral image dataset illustrate the merits of the proposed approach.
收录类别	EI ; CPCI（ISTP）
产权排序	1
会议主办者	The Institute of Electrical and Electronics Engineers, Geoscience and Remote Sensing Society (GRSS)
会议录	2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016
会议录出版者	IEEE
会议录出版地	New York
语种	英语
ISBN号	978-1-5090-3332-4
WOS记录号	WOS:000388114606192
内容类型	会议论文
源URL	[http://ir.sia.cn/handle/173321/19769]
专题	沈阳自动化研究所_机器人学研究室
推荐引用方式 GB/T 7714	He, Shiying,Zhou, Haiwei,Wang Y,et al. Super-resolution reconstruction of hyperspectral images via low rank tensor modeling and total variation regularization[C]. 见:2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016. Beijing, China. July 10-15, 2016.