摘要
针对粒子图像测速(particle image velocimetry,PIV)技术中互相关算法运算量巨大的问题,提出了一种改进的基于快速傅里叶变换(FFT)的互相关算法.改进算法根据频域抽取原理,设置相关窗口重叠率为50%,重叠窗口一个维度的FFT值可由其相邻重叠子窗口的同一维度FFT值经频移叠加获得,无需进行FFT,有效减少了互相关运算中的重复FFT运算量.最后,利用CCD相机连续采集多帧粒子图像进行了算法对比验证及分析.实验结果表明,改进算法在运算效率方面实际提高了约12.25%.
An improved fast Fourier transform（FFT）-based cross-correlation algorithm is proposed to solve the computational efficiency problem of cross-correlation in particle image velocimetry（PIV）.Based on the decimation in frequency theory,when the overlapping correlation window size is about 50%,the one-dimensional FFT values of overlapping windows are composed of their neighbor sub-window′s FFT values by using the frequency shift instead of implementing FFT and the repeating computation in FFT is greatly reduced.Finally,the proposed method was tested with the real particle images continuously acquired by CCD camera.The experimental results show about 12.25% increase in computational efficiency compared with the traditional method.
出处
《大连理工大学学报》
EI
CAS
CSCD
北大核心
2011年第3期417-421,共5页
Journal of Dalian University of Technology
基金
国家自然科学基金资助项目(50879098)
关键词
粒子图像测速
互相关算法
快速傅里叶变换(FFT)
频域抽取
运算效率
particle image velocimetry
cross-correlation algorithm
fast Fourier transform（FFT）
decimation in frequency domain
computational efficiency
