基于Delaunay三角剖分的多相流射线层析成像
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摘要
为提高多相流CT系统重建图像质量,提出基于Delaunay三角剖分的射线层析成像方法。根据模型构造点集,对管道截面进行多尺度Delaunay三角剖分,根据三角形重心在探测阵列上的投影到其最近探测阵列元的归一化距离,确定各剖分单元的投影系数,并采用不同的重建算法进行图像重建。仿真与实验结果表明,该方法可利用少量投影数据重建图像,改善了工业多相流检测中投影数据不完整造成的图像失真;与均匀剖分相比,多尺度剖分明显改进了图像精度和实时性。
In order to improve the image quality of multiphase flow CT system,Delaunay triangulation based CT technique is developed.A point set is constructed based on the model of the imaging region,and multiple dimensioned triangulation for the conduit section is carried out using Delaunay method,then according to the normalized distance between the projection of the triangle gravity center and its nearest detector,the projection coefficient of every triangular cell can be calculated.Thereafter various reconstruction algorithms are utilized to reconstruct the image.Simulation and experiment results demonstrate that the proposed method can reconstruct image from limited projection data,thus can improve the poor image quality caused by the incompleteness of the projection data in industrial multiphase flow measurement,which proves that multiple dimensioned triangulation is superior to uniform tessellation both in image accuracy and real time performance.
In order to improve the image quality of multiphase flow CT system,Delaunay triangulation based CT technique is developed.A point set is constructed based on the model of the imaging region,and multiple dimensioned triangulation for the conduit section is carried out using Delaunay method,then according to the normalized distance between the projection of the triangle gravity center and its nearest detector,the projection coefficient of every triangular cell can be calculated.Thereafter various reconstruction algorithms are utilized to reconstruct the image.Simulation and experiment results demonstrate that the proposed method can reconstruct image from limited projection data,thus can improve the poor image quality caused by the incompleteness of the projection data in industrial multiphase flow measurement,which proves that multiple dimensioned triangulation is superior to uniform tessellation both in image accuracy and real time performance.
引文
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[14]王化祥,王琦,郝魁红.最小交叉熵图像重建算法[J].仪器仪表学报,2009,30(12):2574-2579.WANG H X,WANG Q,HAO K H.Reconstruction ima-ges based on minimum cross-entropy[J].Chinese Jour-nal of Scientific Instrument,2009,30(12):2574-2579.
[15]CHARLES L.BYRNE.Iterativeimagere construction algorithms based on cross-entropy minimization[J].IEEE Transactions onImage Processing,1993,2(1):96-103.
[16]张立峰,王化祥.基于SVM及电容层析成像的两相流流型识别[J].仪器仪表学报,2009,30(4):812-816.ZHANG L F,WANG H X.Identification of two-phaseflow regime based on support vector machine and electri-cal capacitance tomography technique[J].Chinese Jour-nal of Scientific Instrument,2009,30(4):812-816.
[2]成谷,张宝金.三角网格参数化在反射地震走时层析成像中的应用[J].中山大学学报,2006,45(5):128-132.CHENG G,ZHANG B J.Application of triangle cell pa-rameterization in travel-time tomography of reflection seis-mic data[J].Acta Scientiarum Naturalium UniversitatisSunyatseni,2006,45(5):128-132.
[3]李光伟,陈志杰,李建勋.Delaunay三角剖分插值用于超分辨成像[J].电子科技大学学报,2009,38(4):617-620.LI G W,CHEN ZH J,LI J X.Delaunay triangulation in-terpolation used in super-resolution imaging[J].Journalof University of Electronic Science and Technology of Chi-na,2009,38(4):617-620.
[4]CHUANCHU K,HONGTZONG Y.A Delaunay-based region-growing approach to surface reconstruction from unorganizedpoints[J].Computer-Aided Design,2005,37:825-835.
[5]纪凤欣,欧宗瑛,秦绪佳.基于Delaunay三角剖分的层析图像离散数据表面重建算法[J].工程图学学报,2001,2:54-58.JI F X,OU Z Y,QIN X J.An algorithm of reconstruc-ting 3D surface from discrete data of layered images basedon delaunay triangulation[J].Journal of EngineeringGraphics,2001,2:54-58.
[6]YANG D Y,ZHOU B,WANG SH M.Electrical capacitancetomography in dense-phase pneumatic conveying of pulverizedcoal under high pressure[J].Imaging Systems and Tech-niques,2009,(11-12):41-46.
[7]马平,周晓宁,田沛,等.基于COMSOL电容层析成像[J].电测与仪表,2009,46(11):20-23.MA P,ZHOU X N,TIAN P,et al.Electrical capaci-tance tomography based on COMSOL[J].ElectricalMeasurement and Instrumentation,2009,46(11):20-23.
[8]郭建龙,陈世元.一种新型基于Matlab/pdetool的有限元前处理程序开发方法[J].微电机,2007,40(11):78-81.GUO J L,CHEN SH Y.Novel method for programmingof pretreatment of FEM based on Matlab/pdetool[J].Micromotors,2007,40(11):78-81.
[9]MAYER M,HAMEL L A,TOUSIGNANT O,et al.Sig-nal formation in a CdZnTe imaging detector with coplanarpixel and control electrodes[J].Nuclear Instruments andMethods in Physics Research A,1999,(422):190-194.
[10]郝魁红,王化祥,马敏,等.CdZnTe探测器在便携式探测仪中的设计应用研究[J].仪器仪表学报,2007,28(1):95-98.HAO K H,WANG H X,MA M,et al.Design and ap-plication of CdZnTe detector in portable detecting instru-ment[J].Chinese Journal of Scientific Instrument,2007,28(1):95-98.
[11]XU J Q,ZOU R P,YU A B.Analysis of the packingstructure of wet spheres by Voronoi-Delaunay tessellation[J].Granular Matter,2007,(9):455-463.
[12]CONSTANTINIU A,STEINMANN P,BOBACH T,etal.The adaptive delaunay tessellation:a neighborhoodcovering meshing technique[J].Computational Mechan-ics,2008,(42):655-669.
[13]王化祥,唐磊.基于TV正则化算法的电容层析成像自适应剖分方法[J].电子测量技术,2006,29(5):8-11.WANG H X,TANG L.Self-adaptive mesh generation inelectrical capacitance tomography based on total variationregularization algorithm[J].Electronic MeasurementTechnology.2006,29(5):8-11.
[14]王化祥,王琦,郝魁红.最小交叉熵图像重建算法[J].仪器仪表学报,2009,30(12):2574-2579.WANG H X,WANG Q,HAO K H.Reconstruction ima-ges based on minimum cross-entropy[J].Chinese Jour-nal of Scientific Instrument,2009,30(12):2574-2579.
[15]CHARLES L.BYRNE.Iterativeimagere construction algorithms based on cross-entropy minimization[J].IEEE Transactions onImage Processing,1993,2(1):96-103.
[16]张立峰,王化祥.基于SVM及电容层析成像的两相流流型识别[J].仪器仪表学报,2009,30(4):812-816.ZHANG L F,WANG H X.Identification of two-phaseflow regime based on support vector machine and electri-cal capacitance tomography technique[J].Chinese Jour-nal of Scientific Instrument,2009,30(4):812-816.
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