粒子图像测速技术互相关算法研究进展  

RESEARCH PROGRESS OF CROSS CORRELATION ALGORITHMS IN PARTICLE IMAGE VELOCIMETRY

作　　者：张伟[1] 葛耀君[1] 杨詠昕[1] 

机构地区：[1]同济大学土木工程防灾国家重点实验室,上海200092

出　　处：《力学进展》2007年第3期443-452,共10页Advances in Mechanics

基　　金：国家自然科学基金重点项目(50538050);国家高技术研究发展863计划项目(2006AA11Z108);国家自然科学基金项目(50608059)联合资助~~

摘　　要：粒子图像测速技术(particle image velocimetry,PIV)中采用的互相关算法就是需要从独立存在的两幅图像通过一定的判别方法得到流场中各点的流速矢量的计算方法.互相关算法的具体实现步骤包括图像前处理、区域离散、匹配原则选取、搜索方法选取和变形预测,最后对结果进行后处理.文中从上述几个方面总结了国内外近年来互相关算法的发展过程,并通过对各种方法精度和效率的比较对其应用发展进行了归纳.Cross correlation algorithms in particle image velocimetry （PIV） are used to get the full field velocity information of the flow field from the two PIV images. Such an algorithm can be implemented in the following stages： image pre-processing, area discretization, block matching, searching programs setting, image deformation predicting and data post-processing, which are detailed in this paper with related researches during the recent years being reviewed. The spatial resolution and the efficiency of the different algorithms are discussed and compared with each other.

关 键 词：PIV 互相关算法 区域离散 匹配原则 变形预测 

分 类 号：TP311.56[自动化与计算机技术—计算机软件与理论]