基于微粒子群优化算法的数字散斑图像相关方法  

Digital speckle image correlation method base on particle swarm optimization algorithm

作　　者：梁智锦[1] 王开福[1] 顾国庆[1] 张成斌[1] 

机构地区：[1]南京航空航天大学航空宇航学院,南京210016

出　　处：《激光技术》2014年第5期603-607,共5页Laser Technology

基　　金：国防技术基础科研资助项目;江苏省高校优势学科建设工程资助项目

摘　　要：为了能够通过一步搜索同时得到数字散斑图像中所测点的整像素和亚像素位移信息,采用灰度插值的方法构造了亚像素子区,改进了基于微粒子群算法的数字图像散斑相关方法。对含有平移信息的模拟散斑图和具有应变的模拟散斑图进行相关计算,验证了该方法的适用性;在对具有微小面内位移转动的试件进行测量时,比较了整像素的微粒子群算法和不同量级的灰度插值下的亚像素微粒子群算法。结果表明,基于微粒子群算法的亚像素数字散斑图像相关方法在测量小位移方面具有一定的优越性。In order to get the integer pixel displacement information and the sub-pixel displacement information simultaneously at one time, the sub-pixel subarea was constructed by using the method of gray interpolation and the digital image correlation method based on particle swarm optimization algorithm was proposed. The applicability of the method was verified by measuring both the simulated speckle pattern with the translational information and with the strain information. And then, the integer pixel particle swarm algorithm and the sub-pixel of different magnitude interpolation gray particle swarm algorithm were compared by measuring the specimen with tiny rotational displacement. The results show that the particle swarm algorithm based on sub-pixel digital scattered spot image correlation method has advantages for small displacement measurement.

关 键 词：图像处理 数字散斑相关 微粒子群优化算法 灰度插值 

分 类 号：TN911.73[电子电信—通信与信息系统]