缩放比例
稳健性(进化)
算法
各向同性
流离失所(心理学)
旋转(数学)
像素
傅里叶变换
计算机科学
快速傅里叶变换
相位相关
数字图像相关
相关系数
旋转角
数学
光学
人工智能
傅里叶分析
物理
几何学
数学分析
统计
短时傅里叶变换
基因
生物化学
心理学
化学
心理治疗师
作者
Zheng Fang,Yue Gao,Zeren Gao,Yang Liu,Yaru Wang,Yong Su,Qingchuan Zhang
出处
期刊:Applied Optics
[The Optical Society]
日期:2020-10-27
卷期号:59 (33): 10523-10523
被引量:14
摘要
The initial value estimation for seed point is the first step in digital image correlation calculation. Among the existing algorithms, the Fourier–Mellin transform-based cross correlation (FMT-CC) algorithm is one of the most efficient and robust owing to its rotation- and scale-invariance. However, when the displacement is large (more than a hundred pixels), the FMT-CC algorithm fails. In this paper, an automated and efficient initial value estimation method based on an FMT-CC algorithm is presented to deal with large displacement, large rotation, and large isotropic scaling. The relationship between subset size and the maximal displacement in the FMT-CC algorithm is studied, and a strategy of setting the subset size according to the estimated displacement is proposed to improve the robustness of the FMT-CC algorithm. In addition, in cases of large displacement, a multi-scale search method is proposed to improve efficiency. The experimental results show that the proposed methods can realize rapid and automated initial value estimation even under conditions of large displacement, large rotation, and large isotropic scaling. The computational efficiency of the multi-scale search method is about one order of magnitude higher than the traditional FMT-CC method.
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