General Total Variation Minimization Theorem for Compressed Sensing Based Interior Tomography

被引:30
作者
Han, Weimin [1 ]
Yu, Hengyong [2 ]
Wang, Ge [2 ]
机构
[1] Univ Iowa, Dept Math, Iowa City, IA 52242 USA
[2] VT WFU Sch Biomed Engn & Sci, Virginia Tech, Biomed Imaging Div, Blacksburg, VA 24061 USA
关键词
D O I
10.1155/2009/125871
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Recently, in the compressed sensing framework we found that a two-dimensional interior region-of-interest (ROI) can be exactly reconstructed via the total variation minimization if the ROI is piecewise constant (Yu andWang, 2009). Here we present a general theoremcharactering aminimization property for a piecewise constant function defined on a domain in any dimension. Our major mathematical tool to prove this result is functional analysis without involving the Dirac delta function, which was heuristically used by Yu andWang (2009). Copyright (C) 2009 Weimin Han et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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页数:3
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