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	Compressed sensing by inverse scale space and curvelet thresholding
	Jianwei Ma
	2010-10-12 ; 2010-10-12
关键词	Practical/ data acquisition data compression image coding image reconstruction image segmentation reaction-diffusion systems/ compressed sensing curvelet thresholding sampling theory data acquisition compressible signal reconstruction linear measurements reaction-diffusion equations inverse scale space flows medical CT aerospace remote sensing image recovery/ B6135C Image and video coding C5260B Computer vision and image processing techniques C6130 Data handling techniques
中文摘要	Compressed sensing provides a new sampling theory for data acquisition, which says that compressible signals can be exactly reconstructed from highly incomplete sets of linear measurements. It is significant to many applications, e.g., medical imaging and remote sensing, especially for measurements limited by physical and physiological constraints, or extremely expensive. In this paper, we proposed a recovery algorithm from a view of reaction-diffusion equations, by applying curvelet thresholding in inverse scale space flows. Numerical experiments in medical CT and aerospace remote sensing show its good performances for recovery of detailed features from incomplete and inaccurate measurements, in comparison with some existing methods. [All rights reserved Elsevier].
语种	英语
出版者	Elsevier Science Inc. ; USA
内容类型	期刊论文
源URL	[http://hdl.handle.net/123456789/78983]
专题	清华大学
推荐引用方式 GB/T 7714	Jianwei Ma. Compressed sensing by inverse scale space and curvelet thresholding[J],2010, 2010.
APA	Jianwei Ma.(2010).Compressed sensing by inverse scale space and curvelet thresholding..
MLA	Jianwei Ma."Compressed sensing by inverse scale space and curvelet thresholding".(2010).

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