Spline based least squares integration for two-dimensional shape or wavefront reconstruction

In this work, we present a novel method to handle two-dimensional shape or wavefront reconstruction from its slopes. The proposed integration method employs splines to fit the measured slope data with piecewise polynomials and uses the analytical polynomial functions to represent the height changes in a lateral spacing with the pre-determined spline coefficients. The linear least squares method is applied to estimate the height or wavefront as a final result. Numerical simulations verify that the proposed method has less algorithm errors than two other existing methods used for comparison. Especially at the boundaries, the proposed method has better performance. The noise influence is studied by adding white Gaussian noise to the slope data. Experimental data from phase measuring deflectometry are tested to demonstrate the feasibility of the new method in a practical measurement.     

Shape reconstruction from gradient data in an arbitrarily-shaped aperture by iterative discrete cosine transforms in Southwell configuration

The shape reconstruction from gradient data is a common problem in many slope-based metrology applications. In practice, the gradient data may not be ideally available for the whole field of view as expected, due to the aperture or the unmeasurable part of sample. An iterative method by using discrete cosine transforms is addressed in this work to deal with the integration problem with incomplete gradient dataset in Southwell configuration. Simulation indicates that the discrete cosine transform provides better initial values than discrete Fourier transform does, and it converges to a more accurate level by updating with spectrum-based slopes comparing to the slope updates from finite difference in classical method. Experimental results show the feasibility of the proposed approach in a practical measurement.     

The shape gradient of the least-squares objective functional in optimal shape design problems of radiative heat transfer

Optimal shape design problems of steady-state radiative heat transfer are considered. The optimal shape design problem (in the three-dimensional space) is formulated as an inverse one, i.e., in the form of an operator equation of the first kind with respect to a surface to be optimized. The operator equation is reduced to a minimization problem via a least-squares objective functional. The minimization problem has to be solved numerically. Gradient minimization methods need the gradient of a functional to be minimized. In this paper the shape gradient of the least-squares objective functional is derived with the help of the shape sensitivity analysis and adjoint problem method. In practice a surface to be optimized may be (or, most likely, is to be) given in a parametric form by a finite number of parameters. In this case the objective functional is, in fact, a function in a finite-dimensional space and the shape gradient becomes an ordinary gradient. The gradient of the objective functional, in the case that the surface to be optimized is given in a finite-parametric form, is derived from the shape gradient. A particular case, that a surface to be optimized is a “two-dimensional” polyhedral one, is considered. The technique, developed in the paper, is applied to a synthetic problem of designing a “two-dimensional” radiant enclosure.     

Research on three-dimensional shape reconstruction of circular cylindrical flaw

In this article, three-dimensional Born inverse scattering method is modified to convenient form for a cylindrical specimen that includes three-dimensional defect. One aluminum cylinder with flaw model is prepared and ultrasonic measurements are carried out. The measurement area in the modified methods is restricted in the plane perpendicular to the axis of cylindrical specimen. That’s to say that the method is modified to convenient form to use measured waveforms in the x₁ − x₂ plane. The measured wave data are fed into the inversion method and cross-sectional images are obtained. Then, three-dimensional shape reconstruction of flaw model in aluminum specimen is performed by piling up the cross-sectional images. At the same time, we get the numerical results from all directions by finite element method.     

改进的约束共轭梯度闪光照相图像重建算法

针对闪光照相图像信噪比低的特点,提出了一种改进的约束共轭梯度闪光照相图像重建算法。该算法在约束共轭梯度迭代重建的基础上,提出了新的预优矩阵选取方案,减小了重建图像的轴线噪声,利用松弛迭代步长代替共轭梯度法中的最优迭代步长,并采用了新的收敛准则,在保证算法收敛的同时,减少了重建算法的计算量。数值试验表明,与传统约束共轭梯度重建算法相比,改进算法稳定收敛,迭代速度更快,并能有效提高重建质量。     

改进的约束共轭梯度闪光照相图像重建算法

 针对闪光照相图像信噪比低的特点,提出了一种改进的约束共轭梯度闪光照相图像重建算法。该算法在约束共轭梯度迭代重建的基础上,提出了新的预优矩阵选取方案,减小了重建图像的轴线噪声,利用松弛迭代步长代替共轭梯度法中的最优迭代步长,并采用了新的收敛准则,在保证算法收敛的同时,减少了重建算法的计算量。数值试验表明,与传统约束共轭梯度重建算法相比,改进算法稳定收敛,迭代速度更快,并能有效提高重建质量。     

Eigenfunctions of Laplacian for phase estimation from wavefront gradient or curvature sensing

Modal cross coupling usually exists in wavefront estimation through Zernike polynomials. In order to cope with the problem, the eigenfunctions of Laplacian with Neumann boundary condition are proposed instead of Zernike polynomials to reconstruct phase from wavefront gradient or curvature sensing. It is proved theoretically that these modals can avoid modal cross coupling in both wavefront gradient sensing and curvature sensing. In wavefront gradient sensing, the coefficients of eigenfunctions of Laplacian can be obtained from the integral of the scalar product between the gradient of Laplacian's eigenfunctions and wavefront gradient signal. In wavefront curvature sensing, the coefficients of eigenfunctions of Laplacian can be calculated from the integral of the product of Laplacian's eigenfunctions and wavefront curvature signal. This approach is applicable on arbitrary apertures as long as eigenfunctions of Laplacian on apertures of arbitrary shape can be obtained.     

基于数据融合的多变量相空间重构方法

针对单变量时间序列和多变量时间序列相空间重构所存在的问题,提出一种新的多变量融合的相空间重构方法. 通过Bayes估计理论,将多变量在同一相空间中进行相点的最优融合,得到了更为理想的融合相空间. 应用所提出的方法对Lorenz系统及耦合Rssler系统进行了多变量融合的相空间重构. 通过多变量重构图与单变量重构图的比较,发现基于数据融合的多变量相空间重构图包含了所有单变量相空间重构图的重要信息,使重构的相空间更加完备,较全面地反映出吸引子的全貌信息. 最后应用该方法对转子油膜涡动故障得到的多变量时间序列 关键词： 多变量时间序列 相空间重构 数据融合 Bayes估计     

3D shape reconstruction of teeth by shadow speckle correlation method

This paper presents a new method for 3D shape reconstruction in computer-aided dental prosthetics. A specklegram is projected onto the tooth to be measured. This shadow speckle image is recorded and then processed by a digital image correlation method, which enables the computation of 2D shapes based on the similar principle of shadow moiré method. By repeating the procedure for all the sides, i.e., one crown and several side surfaces, local 2D shapes can be measured precisely. Afterwards, these local 2D profiles are merged to form a 3D model, during which certain constraints such as the widths along perpendicular directions are introduced to guide the process. As the height information within an entire image field is recorded instantly, it has the potential to be employed in an intra-oral environment, which would make the patient feel more comfortable during the restoration process. In vitro experiments were carried out on gypsum teeth models and the results proved the effectiveness of the proposed method.     

中子半影成像的两种非线性重建方法研究

对图象重建的分子动力学方法进行了改进,使用能更快收敛的蛙跳格式,并添加规整化项以保持图像细节;同时还对图像重建的共轭梯度方法进行了分析,揭示了它与分子动力学方法的联系和区别;比较了两种方法的重建结果,分析了两种方法对于有噪声图像重建时的优缺点.     

3D shape reconstruction of parabolic trough collector from gradient data based on slope stitching approach

A method based on slope stitching for measurement of a large off-axis parabolic trough collector is proposed and applied to the surface shape reconstructed from the gradient data acquired by using the reverse Hartmann test.The entire reflector is divided into three sections with overlapping zones along the concentration direction.A mathematical model for the slope stitching algorithm is developed.An improved reconstruction method combining Zernike slope polynomials iterative fitting with the Southwell integration algorithm is utilized to recover the real three-dimensional(3 D) shape of the collector.The efficiency and validity of the improved reconstruction method and the stitching algorithm are experimentally verified.     

基于约束共轭梯度的高能闪光照相3维重建算法

针对高能闪光照相系统成像信噪比低的特点,提出了3维约束共轭梯度算法,该算法基于3维重建理论来重建方程,利用约束共轭梯度法迭代求图像重建的最优解。数值模拟结果表明：采用3维约束共轭梯度算法能有效改善高能闪光照相重建图像轴线噪声大的问题,是一种具有很高抗噪能力的闪光照相图像重建算法。     

基于约束共轭梯度的高能闪光照相3维重建算法

 针对高能闪光照相系统成像信噪比低的特点,提出了3维约束共轭梯度算法,该算法基于3维重建理论来重建方程,利用约束共轭梯度法迭代求图像重建的最优解。数值模拟结果表明：采用3维约束共轭梯度算法能有效改善高能闪光照相重建图像轴线噪声大的问题,是一种具有很高抗噪能力的闪光照相图像重建算法。     

Point-based integration for 3D object reconstruction from Ladar range images

A method of point-based integration from multiple registered laser radar (Ladar) range images for 3D object reconstruction is presented in this literature. Our method operates surface point data directly and provides a direct way for overlapping data removal. The overlapping areas were detected using a single distance threshold. In order to set the distance threshold, a local point density approach is introduced to solve it. Compared with the mesh-based, volumetric and other points-based integration approaches, our method is simple and fast, and need less storage memory. The approach is performed on various objects with different geometric shapes. The experimental results demonstrate the efficiency and feasibility of our method.     

Linear method for evaluation of radius of spherical surface from discrete set of data points

Our work deals with the problem of evaluation of the spherical surface parameters from the discrete set of measured data points. We propose a new linear method for determination of the center and the radius of curvature of the measured spherical surface. Such method can be used for evaluation of the measurements obtained from both contact and noncontact 3D coordinate measuring machines. We perform an analysis of the proposed sphere fitting method and we verify that the obtained results are comparable to results calculated using existing techniques. Finally, the proposed algorithm is implemented for evaluation of real measurements of spherical optical surfaces using the designed scanning chromatic confocal system.     

3D reconstruction of nanocrystalline particles from a single projection

This paper describes an approach to retrieve the three-dimensional atomic structure of a nanocrystalline particle from the reconstructed electron exit wave function in a single projection direction. The method employs wave propagation to determine the local exit surface of each atomic column together with its mass. The exit wave in between colums is used as internal calibration so as to remove the background noise and improve the precision to the level of single atom sensitivity. The validity of the approach is tested with exit wave functions of a gold wedge reconstructed from simulated images containing different levels of noise.     

Three-dimensional holographic reconstruction of two-dimensional image information from serial sections and its applications in biomedicine

An experimental study to synthesize holographically two-dimensional projections of serial sections at various depths into three-dimensional images is described. The effects caused by the position, size and resolution of virtual images during reconstruction are analysed, and the advantages and limitations of this method are discussed. An application of this experimental method — the three-dimensional reconstruction of serial sections of a newt embryo — is presented.     

Variational piecewise constant level set methods for shape optimization of a two-density drum

We apply the piecewise constant level set method to a class of eigenvalue related two-phase shape optimization problems. Based on the augmented Lagrangian method and the Lagrange multiplier approach, we propose three effective variational methods for the constrained optimization problem. The corresponding gradient-type algorithms are detailed. The first Uzawa-type algorithm having applied to shape optimization in the literature is proven to be effective for our model, but it lacks stability and accuracy in satisfying the geometry constraint during the iteration. The two other novel algorithms we propose can overcome this limitation and satisfy the geometry constraint very accurately at each iteration. Moreover, they are both highly initial independent and more robust than the first algorithm. Without penalty parameters, the last projection Lagrangian algorithm has less severe restriction on the time step than the first two algorithms. Numerical results for various instances are presented and compared with those obtained by level set methods. The comparisons show effectiveness, efficiency and robustness of our methods. We expect our promising algorithms to be applied to other shape optimization and multiphase problems.     

两种M2因子实验测量方法的比较

为了从实验上分析和验证H-S传感器测量M2因子方法,对使用双曲线拟合法测量M2因子和H-S传感器测量M2因子做了详细的实验研究,且对实验结果、实验误差进行了比较与分析。研究表明:当H-S波前传感器透镜组足够多,重构误差较小,选取合适的泽尼克多项式阶数时,H-S波前传感器一次测量法得到的光束的M2因子与传统方法测得的M2因子值基本相当。与双曲线拟合法相比,H-S传感器法适用范围小,但是当满足测量条件时,H-S传感器法更便捷。     

The use of multivariate MR imaging intensities versus metabolic data from MR spectroscopic imaging for brain tumour classification

This study investigated the value of information from both magnetic resonance imaging and magnetic resonance spectroscopic imaging (MRSI) to automated discrimination of brain tumours. The influence of imaging intensities and metabolic data was tested by comparing the use of MR spectra from MRSI, MR imaging intensities, peak integration values obtained from the MR spectra and a combination of the latter two. Three classification techniques were objectively compared: linear discriminant analysis, least squares support vector machines (LS-SVM) with a linear kernel as linear techniques and LS-SVM with radial basis function kernel as a nonlinear technique. Classifiers were evaluated over 100 stratified random splittings of the dataset into training and test sets. The area under the receiver operating characteristic (ROC) curve (AUC) was used as a global performance measure on test data. In general, all techniques obtained a high performance when using peak integration values with or without MR imaging intensities. For example for low- versus high-grade tumours, low- versus high-grade gliomas and gliomas versus meningiomas, the mean test AUC was higher than 0.91, 0.94, and 0.99, respectively, when both MR imaging intensities and peak integration values were used. The use of metabolic data from MRSI significantly improved automated classification of brain tumour types compared to the use of MR imaging intensities solely.