级数相位去包裹方法

提出了一个简单的相位去包裹方法－－条纹的极数相位去包裹算法,将其用来恢复物体的真实相位。与传统的条纹相位去包裹方法相比较,该方法能够消除光载频、物体边缘、阴影和盲点的影响。理论分析和实验结果证明该方法适用于条纹空间相位测量方法解调的包裹相位。     

基于可靠性的相位去包裹算法

提出了一种新的基于可靠性的相位去包裹算法。采用了队列算法及去包裹可靠性的判别标准。与传统方法相比,能够自动避开噪声区域,解决了相位去包裹中的阴影遮挡以及空洞等问题,克服了传统去包裹方法中的误差传播效应,能准确快速地对全场进行相位去包裹。设计了一套基于此算法的三维形面测量系统。     

相位图去包裹方法及其进展

近年来付立叶变换法和相移法在辅助光学测量中得到了广泛的应用,但处理后的相位图一般包裹在[-π,π)间,要获得正确的物理变化信息,需要对原始相位图进行去包裹运算。相位去包裹算法主要有传统算法、分割线算法、最小二乘算法、细胞自动机算法、付立叶变换算法、质量导向图算法等。本文较详细地阐述了几种相位去包裹算法的数学模型和基本原理及其最新进展,分析了各自的优缺点及其适用范围。     

基于双频彩色条纹投影的相位测量去包裹方法

为了提高测量速度,提出一种基于双频彩色条纹投影的相位测量去包裹方法,只需采集一帧图像,就能实现高速测量以及动态物体轮廓测量中的相位去包裹。论述了双频相位测量和变精度去包裹原理,并详细分析影响测量精度的因素。该方法采用计算机生成一帧双频双色正弦条纹图,用液晶数字投影仪投影,并用傅里叶变换的方法对两个单色条纹图进行分析,获得高低两种精度的被测物体高度信息,从而进行变精度去包裹处理。结果表明,利用该方法提高了测量速度,可得到较高的去包裹精度,其测量最大绝对误差为 1．413～-1．582 mm,标准差为0．363 mm。     

运用泽尼特多项式的相位去包裹算法

提出了一种新的相位去包裹算法，主要针对光学光滑表面以及由于少数低调制度点、散斑点、噪声或灰尘（以下简称误差点）引起的去包裹失败的情形。该算法运用泽尼特（Ｚｅｒｎｉｋｅ）多项式对误差点区域进行拟合，通过一定阈值的设置，将误差点清除并予以拟合，具有计算快速的特点。     

一种基于图像融合和卷积神经网络的相位恢复方法

相位恢复法利用光波传输中某一(或某些)截面上的光强分布来传感系统波前,其结构简单,不易受震动及环境干扰,被广泛应用于光学遥感和像差检测等领域.传统相位恢复法采用迭代计算,很难满足实时性要求,且在一定程度上依赖于迭代转换或迭代优化初值.为克服上述问题,本文提出了一种基于卷积神经网络的相位恢复方法,该方法采用基于小波变换的图像融合技术对焦面和离焦面图像进行融合处理,可在不损失图像信息的同时简化卷积神经网络的输入.网络模型训练完成后可依据输入的融合图像直接输出表征波前相位的4-9阶Zernike系数,且波前传感精度均方根(root-mean-square,RMS)可达0.015λ,λ=632.8 nm.研究了噪声、离焦量误差和图像采样分辨率等因素对波前传感精度的影响,验证了该方法对噪声具有一定鲁棒性,相对离焦量误差在7.5%内时,波前传感精度RMS仍可达0.05λ,且随着图像采样分辨率的提升,波前传感精度有所改善,但训练时间成本随之增加.此外,分析了实际应用中,当系统像差阶数与网络训练阶数略有差异时,本方法所能实现的传感精度,并给出了解决方案.     

双频相位测量轮廓术及其误差分析

提出一种双频相位测量轮廓术，利用这一技术。在相位恢复过程中，对有断点及边界区域也能得到正确的去包裹相位值，把这一技术用于三维面形测量中，得到了较好的实验结果。最后，分析实验产生误差的原因。     

数字散斑相位图去包裹新算法

提出了一种新的数字散斑相位图去包裹算法,主要针对检测对象为复杂非连续物体这一情况。物体在激光照明下,采用光学相位反相相减图像的方法来检测并标识出相位间断区,并利用改进了的行列去包裹算法。使去包裹过程只在相位有效区域进行,从而准确快速地实现全场有效区域的相位去包裹。与已提出的相位去包裹方法相比,该算法具有计算量小,速度快,并能有效地避开大面积的相位间断区的优点,该方法使数字散斑技术可以方便地应用于工程实际中如对复杂非连续构件的变形、振动等方面的定量分析。     

一种用于三维面形测量的新的去包裹方法

本文提出一种可用于三维面形测量的新的去包裹方法。它在原有传统去包裹的基础上提出分割线的方法,能够正确标出应该参与去包裹的象素点及由噪音造成的相位不连续点,因而,在相位图存在噪音及信噪比较低的情况下仍旧可以得到正确且唯一的去包裹相位值。在三维面形测量中,去包裹后的相位值可以真实反映待测物体的面形,因此有很大的理论价值及实际意义。     

基于压缩传感的纯相位物体相位恢复

传统的相位恢复算法通过双强度或者单强度测量的数据进行迭代运算以恢复丢失的相位信息, 它要求采样数据必须满足香农采样定理.当成像的分辨率较高时, 大量的测量数据势必会对数据采样设备提出更多的要求.因此, 为减少采样负担, 本文提出了一种基于压缩传感的相位恢复算法, 通过在傅里叶面的少量单强度测量数据, 应用改进的混合输入输出算法来恢复纯相位物体的相位分布.在采样数据远小于采样定理所需的条件时, 该算法仍能精确地恢复相位分布具有分块均匀特征的纯相位物体.数值仿真实验表明该算法具有良好的收敛性能. 关键词： 相位恢复 压缩传感     

A temporal phase unwrapping algorithm for photoelastic stress analysis

Photoelastic stress analysis is a full-field optical technique for experimental stress analysis whose automation has received considerable research attention over the last 15 years. The latest developments have been made possible largely due to the availability of powerful calculators with large memory capacity and colour, high resolution, cameras. A further stimulus is provided by the photoelastic resins now used for rapid prototyping. However, one critical aspect which still deserves attention is phase unwrapping. The algorithms most commonly used for this purpose have been developed in other scientific areas (classical interferometry, profilometry, moiré, etc.) for solving different problems. In this article a new algorithm is proposed for temporal phase unwrapping, which offers several advantages over those used today.     

最小二乘相位解包络方法

介绍一种最小二乘解相位包络的方法 ,该法的优点在于把图像作为一个整体处理 ,图像上每一个像素点的值由方程唯一确定 ,而且解得的相位图与原包裹的相位图偏差平方加权最小 ,具有局部解相法所不具有的优点。实验证明 ,它能够处理局部处理方法难以解决的相位图 ,并给出几幅实际相位图的处理结果     

A generalized temporal phase unwrapping algorithm for three-dimensional profilometry

A generalized temporal phase unwrapping algorithm is proposed for absolute phase measurement of object surfaces with complex topography. We first make comments on error analysis of various temporal phase unwrapping (TPU) algorithms and point out problems existing in these techniques. We present a generalized TPU algorithm (GTPU), which eliminates some limitations imposed on the fringe sequence for the classical TPU algorithms. So the desired number of fringes can be determined according to practical situation, leading to a flexible method for phase reconstruction. In addition, compared with the classical TPU algorithms, GTPU has better noise immunity and less computational complexity. Theoretical analysis and experiment results are presented to show the validity of the proposed algorithm.     

基于小波变换的最小二乘相位解缠算法

最小二乘法是求解二维相位解缠问题最稳健的方法之一,其本质是在最小二乘意义下使缠绕相位的离散偏导数与解缠相位的偏导数整体偏差最小,并等效为可求解一大型的稀疏线性方程系统。由于系统矩阵结构的稀疏性,在采用迭代法求解时收敛速度非常慢。为了改善收敛特性,提出一种基于多分辨率表示的离散小波变换相位解缠算法。利用小波变换将原线性系统转化成具有较好收敛条件的等价新系统。仿真实验表明,该方法能够很好的恢复真实相位,其解缠效果优于Gauss-Seidel松弛迭代和多重网格法。     

含噪声包裹相位图的加权最小二乘相位展开算法研究

二维相位展开广泛应用在精密光学测量、自适应光学、合成孔径雷达、图像处理等领域中。为处理含噪声包裹相位图,以预条件共轭斜量法求解权重最小二乘相位展开方程。引入非加权二维离散余弦变换求解泊松方程得到的最小二乘相位解作为共轭斜量法的初始解,从而加快了收敛速度,同时提出一种新质量图确定算法求解过程中的权重项。计算机模拟和试验表明算法计算速度快,能有效地消除传统路径积分法在处理信噪比低包裹相位图时的"拉线"现象,是一种有效的相位展开方法。     

应用时域相位解包方法的三维形貌测量系统

设计一套基于时域相位解包方法的三维形貌测量系统 ,克服了传统解包方法中的误差传播效应 ,可以应用于复杂物体表面及复杂环境下的三维形貌测量。由计算机生成光栅并通过液晶投影仪投射到待测物体表面 ,用CCD摄像机采集图像并通过图像采集卡存贮到计算机中进行处理 ,实现了测量的自动化 ,完成一次高精度的测量仅需几秒钟时间。用两个特殊的人头像完成的实验证明了系统的优越性     

Phase unwrapping based on a parallel noise-immune algorithm

A newly developed path-independent phase unwrapping algorithm, which is simple and concise, is presented. The algorithm is based on a parallel elimination of local phase jumps and the subsequent shifts of them, through iterations, to the boundary or to cancel with others in the midway. The number of iterations never exceeds the sum of the width and height of the processed map, whereas for cellular automata algorithm, a multiplier of the cycle of iterations by the proposed algorithm herein is easily needed for successful treatment of a same map. The proposed noise-immune algorithm is applied to a phase map of electronic speckle pattern interferometry (without any filtering work) to prove its effectiveness.     

Noise immune unwrapping based on phase statistics and self-calibration

Unwrapping is an important step for precise phase measurement in an interferometric technique. Due to the effects of noises and speckles, an accurate unwrapping has been quite difficult. To address this issue, a new phase unwrapping method is proposed. The new method uses the wrapped phase statistics together with the limited smoothness characteristics of the interference phase. In this method, statistical parameters of the wrapped phase are firstly obtained. The step is then followed by a self-calibration process to identify and correct corrupted data points to obtain preliminary unwrapped phases. Finally, a phase revision step is taken to remove the effects of the residual errors. A computational testing was carried out to demonstrate the performance of the proposed method at six different levels of noise injection. An experimental test was also carried out using a lateral shearing interferometer. The success and the precision achieved using the proposed algorithm show that the method is quite effective and accurate for phase recovery under the condition of noise contaminations.     

A novel algorithm for branch cut phase unwrapping

Branch cut method is a powerful noise-immune algorithm for correct phase unwrapping of noisy phase maps. The shortest branch cut length promises the optimal unwrapping result of the wrapped phase maps. A new algorithm is proposed to search for the shortest branch cut length by simple exchange operation. Although the algorithm is on the basis of stochastic search techniques, it has a high probability of finding the shortest branch cut length or an approximation of it. Compared with the traditional algorithms, the algorithm is fast and competitive.