一种迭代的锥束计算机层析成像系统几何全参数标定方法

发布时间：2018-06-04 17:50

本文选题：成像系统 + 几何参数标定　；参考：《光学学报》2017年08期

【摘要】：计算机层析成像(CL)系统对于扁平状物体的检测具有独特的优势,几何参数标定是CL系统获得高质量图像的重要步骤。现有CL系统几何参数标定方法仅能标定部分几何参数,难以一次完成所有几何参数的标定。借鉴计算机断层成像(CT)系统几何参数标定方法,提出了一种高精度的迭代标定方法,利用简单体模快速标定CL系统的所有几何参数。对CT系统几何参数标定方法用于CL系统的有效性进行分析,确定对CT系统几何参数标定方法敏感的CL系统几何参数;根据CL系统投影几何关系,构建新的反映CL实际系统与理想系统间误差的非线性最小二乘目标函数,利用迭代法不断优化敏感参数和其他关键参数。实验结果表明,本文方法能够有效标定CL系统所有几何参数,敏感参数以及受敏感参数影响的其他几何参数标定精度均有明显提升。利用已标定的几何参数重建三维Shepp-Logan体模和印刷电路板体模,重建图像中没有几何伪影,验证了算法的有效性。
[Abstract]:Computer tomography (CL) system has a unique advantage for the detection of flat objects. The calibration of geometric parameters is an important step for the CL system to obtain high quality images. The existing geometric parameter calibration method of the CL system can only calibrate some geometric parameters, and it is difficult to calibrate all the parameters at one time. The computer tomography (CT) system is used for reference. A high precision iterative calibration method is put forward to calibrate the geometric parameters of the CL system. The geometric parameter calibration method of the CT system is used to analyze the validity of the CL system, and the geometric parameters of the CL system which are sensitive to the calibration method of the geometric parameters of the CT system are determined, and the projection of the CL system is projected. A new nonlinear least square objective function which reflects the error between the CL system and the ideal system is constructed. The iterative method is used to optimize the sensitive parameters and other key parameters continuously. The experimental results show that the method can effectively calibrate all geometric parameters, sensitization parameters and other geometry affected by sensitive parameters of the CL system. The calibration accuracy of the parameters has been improved obviously. Using the calibrated geometric parameters to reconstruct the 3D Shepp-Logan body model and the printed circuit board model, there is no geometric artifact in the reconstructed image, and the validity of the algorithm is verified.
【作者单位】：信息工程大学信息系统工程学院;
【基金】：国家自然科学基金(61372172,61601518)
【分类号】：TP391.41

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