Virtual sensors for 2D vector field tomography

被引:4
|
作者
Giannakidis, Archontis [2 ]
Kotoulas, Leonidas [1 ]
Petrou, Maria [1 ]
机构
[1] Univ London Imperial Coll Sci Technol & Med, Dept Elect & Elect Engn, London SW7 2AZ, England
[2] Univ Surrey, Fac Engn & Phys Sci, Guildford GU2 7XH, Surrey, England
基金
英国工程与自然科学研究理事会;
关键词
SIGNAL-DEPENDENT NOISE; KERR-EFFECT TOMOGRAPHY; TRACE TRANSFORM; RECONSTRUCTION; VELOCITY; FLOW; DISTRIBUTIONS; IMAGES; OCEAN;
D O I
10.1364/JOSAA.27.001331
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
We consider the application of tomography to the reconstruction of 2-D vector fields. The most convenient sensor configuration in such problems is the regular positioning along the domain boundary. However, the most accurate reconstructions are obtained by sampling uniformly the Radon parameter domain rather than the border of the reconstruction domain. This dictates a prohibitively large number of sensors and impractical sensor positioning. In this paper, we propose uniform placement of the sensors along the boundary of the reconstruction domain and interpolation of the measurements for the positions that correspond to uniform sampling in the Radon domain. We demonstrate that when the cubic spline interpolation method is used, a 60 times reduction in the number of sensors may be achieved with only about 10% increase in the error with which the vector field is estimated. The reconstruction error by using the same sensors and ignoring the necessity of uniform sampling in the Radon domain is in fact higher by about 30%. The effects of noise are also examined. (C) 2010 Optical Society of America
引用
收藏
页码:1331 / 1341
页数:11
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