数字图像相关技术中散斑质量评价标准的研究

发布时间：2019-03-17 11:29

【摘要】：数字图像相关方法作为一种非接触、非干涉的全场光学测量技术,业已广泛应用于实验力学领域形貌、运动和变形的测量,并由于其简单实用性获得越来越广泛的关注。数字图像相关方法如今非常成熟,己涌现出诸多界面友好、功能强大的商业软件。由于数字图像相关方法是基于跟踪测量试件表面的纹理特征,故而散斑图案对数字图像相关方法至关重要。遗憾的是,当前实验采用的散斑仍缺乏统一的制作规范,不同学者采用的散斑不同,不同商业公司推荐的散斑也不同,一线实验人员莫衷一是、难以抉择甚至无法判定哪种散斑效果更好。该现象的产生原因在于完备散斑标准的缺失。因为最优化的散斑应对应着最小化的计算误差,所以完备的散斑质量评价标准的提出应基于对数字图像相关计算误差的深入理解。虽然经过了十几年的研究,对数字图像相关中插值误差导致的系统误差的深层物理机制仍然不明,理论分析遇到相当大的阻力,插值偏差的简单有效的估计算法仍不存在,插值偏差是提出完备散斑质量评价标准的瓶颈。对于同样是系统误差的噪声引入偏差,现有的评价算法也存在诸多不足,根本无法适用于当前广泛采用的B样条、O-MOMS等高精度的广义型插值算法。本人博士期间工作的目标在于攻克插值偏差问题,提出适用于广义型插值算法的噪声引入偏差估计公式,综合考虑随机误差和系统误差提出一种完备的散斑质量评价标准。本文取得的主要成果如下：(1)在插值偏差方面,推导了连续和离散信号插值偏差的解析表达式,揭示了插值偏差的深层物理本质,提出插值偏差核的概念,表明插值偏差由插值偏差核与图像功率谱乘积的积分决定,提出了一种简单、快速、有效的插值偏差估计算法。在数字图像相关领域首次引入随机积分法,将插值偏差降低1个数量级。(2)在噪声引入偏差方面,提出了更广义、更简洁、更优美的噪声引入偏差理论体系,提出一种简单有效的噪声引入偏差估计算法,直观解释了噪声引入偏差的产生原因。(3)在随机误差方面,推导了非均匀噪声情况下数字图像相关随机误差的解析表达式,并通过真实实验进行了验证。(4)在散斑质量评价方面,综合插值偏差、噪声引入偏差和随机误差的理论结果,推导了数字图像相关总误差的解析表达形式,提出了完备的散斑质量评价标准。
[Abstract]:As a non-contact, non-interference all-field optical measurement technique, digital image correlation method has been widely used in the measurement of morphology, motion and deformation in the field of experimental mechanics, and has been paid more and more attention because of its simplicity and practicability. Digital image correlation methods are now very mature, has emerged a number of user-friendly, powerful commercial software. Because the digital image correlation method is based on tracking and measuring the texture features of the specimen surface, speckle pattern is very important to the digital image correlation method. Unfortunately, the speckle used in the current experiment still lacks a unified production standard, different scholars adopt different speckles, and different commercial companies recommend different specks, and there is no agreement among the front-line experimenters. It is difficult to decide even which speckle works better. The reason for this phenomenon lies in the lack of complete speckle criteria. Because the optimal speckle should correspond to the minimized calculation error, the complete speckle quality evaluation standard should be based on the deep understanding of the digital image correlation calculation error. Although after more than ten years of research, the deep physical mechanism of the system error caused by interpolation error in digital image correlation is still unknown, the theoretical analysis encountered considerable resistance, and the simple and effective estimation algorithm of interpolation error still does not exist. Interpolation deviation is the bottleneck to put forward complete speckle quality evaluation standard. For the error introduced by the noise which is also the systematic error, the existing evaluation algorithms also have many shortcomings, so they can not be applied to the high-precision generalized interpolation algorithms such as B-spline, O-MOMS and so on, which are widely used at present. The purpose of my doctor's work is to solve the problem of interpolation deviation, and to propose a noise-introduced error estimation formula which is suitable for generalized interpolation algorithms. A complete speckle quality evaluation standard is put forward considering random errors and systematic errors. The main results obtained in this paper are as follows: (1) in respect of interpolation deviation, the analytical expressions of interpolation deviation of continuous and discrete signals are derived, the deep physical essence of interpolation deviation is revealed, and the concept of interpolation deviation kernel is put forward. It is shown that the interpolation deviation is determined by the integral of the product of the interpolation deviation kernel and the power spectrum of the image. A simple, fast and effective interpolation deviation estimation algorithm is proposed. The random integration method is introduced for the first time in the field of digital image correlation, which reduces the interpolation deviation by one order of magnitude. (2) in the aspect of noise introduction deviation, a more generalized, concise and graceful noise introduction deviation theory system is proposed. In this paper, a simple and effective error estimation algorithm for noise introduction is proposed, which can directly explain the cause of noise error. (3) in the case of random error, the analytic expression of correlation random error for digital image is derived in the case of non-uniform noise. Finally, it is verified by real experiments. (4) in speckle quality evaluation, the theoretical results of interpolation deviation, noise introduced deviation and random error are integrated, and the analytical expression of total error related to digital image is deduced. A complete speckle quality evaluation standard is proposed.
【学位授予单位】：中国科学技术大学
【学位级别】：博士
【学位授予年份】：2016
【分类号】：O348.1

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