DVC中内部散斑质量评价及计算体素点的优化选择

INTERNAL SPECKLE PATTERN QUALITY ASSESSMENT AND OPTIMAL SELECTION OF VOXEL POINTS FOR DIGITAL VOLUME CORRELATION

数字体图像相关方法(digital volume correlation,DVC)是一种可测量物体内部三维全场变形的先进实验力学测试技术,通过分析由体图像成像设备(如X-ray CT)获取的物体变形前后的三维体图像,DVC可获得物体内部具有亚体素精度的三维变形信息.在应用DVC测量内部变形时,被测试样体图像的内部散斑质量对其测量精度有着重要影响.本文从DVC算法位移测量误差的理论分析和数值模拟实验两方面证实了DVC的位移测量误差与计算子体块的灰度梯度平方和(sum of square subvolume intensity gradient,SSSIG)值呈负相关关系,即:计算子体块的SSSIG值越大,其位移测量精度越高,因此SSSIG可用于体图像内部散斑质量的定量评价.尽管直接增加计算子体块尺寸可以增加SSSIG,但是较大计算子体块内更多的计算点会导致计算量的显著增加.为此,本文进一步提出一种计算体素点优化选择方法,该方法通过将计算子体块中灰度梯度较小的体素点剔除出计算,以实现在增大计算子体块尺寸的同时不会显著增加计算量.模拟和真实实验结果显示了该计算体素点优化选择方法的有效性.

Digital volume correlation(DVC)is a powerful experimental tool for quantitative 3D internal deformation measurement throughout the interior of materials or biological tissues.By comparing the volumetric images acquired at the reference and deformed states by a volumetric imaging facility(e.g.,X-ray CT),DVC provides full-field displacements with subvoxel accuracy and full-field strain maps.When using DVC method for internal deformation measurement,the quality of internal speckle pattern of a test sample has an important impact on the accuracy and precision of the measured displacements.In this work,theoretical analysis and numerical simulation experiments are firstly performed to assess the quality of internal speckle patterns.The results show that the displacement measurement error of DVC is negative correlation with the sum of square of subvolume intensity gradient(SSSIG)of a subvolume.Thus,the SSSIG value of a subvolume can be used as a simple and effective metric for quality assessment of its internal speckle pattern.In practical DVC analyses,increasing the SSSIG parameter of a subvolume helps to improve the measurement accuracy and precision of DVC.Despite the SSSIG in a subvolume can be increased by enlarging its subvolume size,this simple approach,however,would lead to increased calculation burden.With a purpose to increase SSSIG without significantly increase the amount of calculation,this paper further proposes a method for optimal selection of calculation voxel points in subvolumes.Specifically,the voxel points with small gray gradients in a subvolume are excluded from DVC calculation to decrease the amount of calculation when increasing the size of the subvolume.The efficacy of the presented voxel point optimal selection method is validated by analyzing computer simulated and experimentally obtained volume images.Experimental results reveal that the proposed voxel point selection method is capable of reducing the calculation burden when increasing the subvolume size to increase the SSSIG parameters.