GPU 加速的路径依赖数字图像相关法

对于数字图像相关法(digital image correlation, DIC)计算效率的需求日益增长,提出了一种图形处理器(GPU)加速的路 径依赖 DIC 方法。 该算法利用基于快捷傅里叶变换的互相关算法(FFT-CC)计算初始种子点,利用反向组合高斯牛顿法( IC-GN)进行亚像素匹配,然后通过初值传递策略快速产生多个新种子点参与亚像素匹配的并行计算,从而使其快速扩散,直至完 成整个感兴趣区域的计算。 利用公开的实验图例进行测试,结果表明方法精度良好,能得到清晰的表面变形云图,并且能在子 区大小 17×17 pixels 时获得 6. 5×10 5 点/ s 的计算速度,相对于典型的高速 DIC 算法速度提升超过 50%,为高速 DIC 算法的设计 提供了参考。

Path-dependent digital image correlation based on GPU acceleration

The demands for computing efficiency of digital image correlation (DIC) is increasing, a GPU-accelerated path-dependent DIC method is proposed. This algorithm uses FFT-CC algorithm to calculate the initial seed points and IC-GN method to carry out sub-pixel registration. Then, through the initial value transfer scheme, multiple seed points are generated to participate in the parallel calculation of sub-pixel registration, so that the calculation points can be rapidly spread until the region of interest is completed. Experiment results show that, the proposed method has a good accuracy and can obtain a clear surface deformation nephogram. It achieves a computing speed of 6. 5×10 5 points per second with a subset size of 17×17 pixels. Compared with typical high-speed DIC algorithm, the speed enhancement is over 50%. It provides reference for the design of high speed DIC algorithm.