光学偏折子孔径拼接面形检测技术

针对大口径的高斜率动态范围光学元件的测量需求,提出了基于光学偏折技术的子孔径拼接测量方法。利用所搭建的条纹投影光学偏折测量系统,结合子孔径划分拼接方法,对各子孔径分别进行测量,并根据实际测量结果与测量系统模型光线追迹结果的偏差,高精度测得各个子孔径的面形数据,由此对各子孔径进行拼接来实现全口径面形测量。光学偏折测量技术相对干涉法具有很大的测量动态范围和视场,可极大降低所需的子孔径数量,由此大大提高了检测效率。同时提出了针对重叠区域的加权融合算法来实现拼接面形的平滑过渡。为验证所提出方案的可行性,分别进行了仿真分析以及实验验证。对一高斜率反光灯罩进行拼接测量实验,并将拼接测量与全口径测量结果进行对比。结果表明,利用所提出测量方法获得的拼接面形连续光滑,且与全口径测量面形RMS值偏差为0.0957 μm,优于微米量级。该测量具有较高的测量精度和大动态测量范围,并且系统结构简单,为各类复杂光学反射元件提供了一种有效可行的检测方法。     

改进最佳缝合线的红外图像拼接方法

变电站场景的红外图像受噪声干扰大、纹理信息不明显,拼接过程中易出现拼接痕迹或重影现象。针对上述问题,本文提出一种改进最佳缝合线的红外图像拼接方法。该方法首先采用SIFT算法提取图像区域特征,实现图像配准;然后在两幅图像的重合区域上引入局部权重系数,并对图像颜色差异强度进行形态学操作,减少红外图像的噪声干扰,以此改善能量函数图的纹理信息。最后,利用动态规划改进缝合线搜索准则,在图像重叠区域搜索出最佳缝合线。实验结果表明,与渐入渐出法和最佳缝合线法比较,本文方法在拼接后图像的平均梯度、图像清晰度和图像边缘强度均有所提高,融合区域过渡更平滑自然,拼接痕迹明显减少。     

FTP中采用双帧条纹消除阴影影响的高度拼接讨论

在FTP测量中,阴影和条纹断裂会影响到正确三维面形的恢复,本文采用两帧条纹来避免阴影对物体面形恢复的影响.提出利用调制度信息来确定从两帧条纹图中恢复的高度图像的拼接区域,并用最小二乘法进行拼接的方法.既避免了阴影对测量的影响,增大了FTP的测量范围,又提高了测量精度.通过实验验证,此方法能有效性地重建具有陡峭变化物体的三维面形.     

光机集成仿真前处理中点云边界检测技术

为解决通用光机集成仿真接口中光学面形点云数据处理问题,提出了基于点云边界检测技术的面形数据前处理方法。首先讨论了集成仿真面形数据前处理方法及边界检测技术在前处理中作用;然后研究了边界检测算法涉及的光学面形点云数据组织,面形节点K邻域微切平面的拟合算法以及边界节点的判断方法。在点云边界检测算法研究基础上,讨论了算法主要数据结构和程序实现,并通过示例面形点云边界提取验证了算法的正确性和有效性,为光机集成仿真面形数据处理算法提供了新的技术参考。     

大口径凸非球面反射镜子孔径拼接检测

为了获得大口径凸非球面反射镜全口径的面形,提出了利用子孔径拼接检测大口径凸非球面的新方法。利用干涉仪标准球面波前依次干涉测定大口径镜面上各个区域的相位分布,通过子孔径拼接算法即可求解得到镜面全口径面形信息。对该方法的基本原理和实现步骤进行了分析和研究,建立了大口径拼接检测算法的数学模型,设计并研制了大口径反射镜拼接检验装置。结合实例对一口径为260 mm 的碳化硅凸非球面反射镜进行了9 个子孔径的拼接干涉测量,并将拼接检测结果与全口径面形测量结果进行对比,两种方法测量面形PV 值和RMS 值的偏差分别为0.043和0.021（=632.8 nm）。     

高精度子孔径拼接中参考面误差的去除方法

基于最小二乘拟合的传统干涉子孔径拼接方法实现了小口径干涉仪对大口径光学元件的检测,然而在子孔径测试过程中,由于干涉仪上的参考面存在面形误差,将使获得的各子孔径的面形数据偏离真实值,所以在进行高精度面形测量时,获得参考面的面形误差并将其补偿掉是非常必要的。因此,提出了一种在拼接过程中用Zernike项对子孔径间重叠区域数据进行拟合的方法来求得参考面面形。首先在传统的目标函数上加入一系列Zernike项表征待求参考面,然后按照最小二乘法对函数进行求解得到各项系数,从而得到拟合的参考面。对平面和球面分别进行了子孔径拼接实验,拟合得到的参考面面形与QED拼接干涉仪计算得到的参考面面形的PV值偏差小于5nm,RMS值偏差小于0.2nm,拼接后的重叠区域不匹配误差值小于10nm。实验结果表明,在子孔径拼接过程中可以补偿参考面误差而得到更真实的拼接面形。     

基于旋转台参数标定实现多视角点云拼接

针对如何方便快捷且准确地获取物体完整面形三维点云数据的问题,提出一种利用旋转台参数标定结果辅助实现多视角三维点云粗拼接的新方法。该方法将一个二维标定靶作为坐标系转换桥梁,仅需两个位置的坐标系关系,即可建立转台转角和不同局部测量坐标系之间的非线性模型,实现对多个测量视角下三维点云的粗配准,为最近点迭代(ICP)算法提供了良好的初值,增加了ICP算法的稳健性。实验表明该方法操作简便、快捷、易实现,拼接后点云误差不大于0.12 mm。     

应用于无人机平台的红外图像拼接技术研究

利用非制冷长波红外热像仪设计了红外图像拼接系统,提出可以应用于无人机平台的红外图像拼接方法。目前的红外图像拼接方法基本都是对经过亮度和对比度增强处理的图像进行拼接,当采集图像的场景不同时待拼接红外图像之间会存在亮度差异,导致最终拼接图像中存在明显接缝。为解决此问题,提出改进的红外图像拼接算法,对未经过亮度及对比度调整的14 bit红外图像进行拼接,然后对拼接图像进行畸变校正,最后将14 bit拼接图像通过平台直方图均衡算法压缩到8 bit灰度范围显示,提高红外拼接图像的对比度。实验结果表明:当相邻两幅待拼接图像的重叠视场不小于单幅红外图像视场的15%时,该方法具有较好的场景适应性,可以实现红外图像无缝拼接,拼接图像重叠区域过渡平滑,畸变校正后的拼接图像更加符合真实场景。     

基于FPGA 的大视场图像实时拼接技术的研究与实现

鉴于目前普遍采用软件方法获得大视场视频图像操作不便且实时性受限的缺陷,研究并设计了一种基于FPGA的可编程技术来实现多个摄像头视频数据实时拼接的大视场成像系统。系统通过APTINA公司的彩色CMOS图像传感器MT9M034获取原始视频图像信息,以Xilinx公司的Virtex-5系列FPGA为核心完成视频数据的实时采集、缓存、拼接及传输。图像拼接部分首先对原始图像进行亮度差异自动调节的预处理以提高整体的拼接效果,然后利用相位相关法完成相对平移量信息检测,对原始图像进行配准,最后采用线性加权融合算法对相邻两幅图像的重合区域进行融合处理,使拼接之后的大视场图像达到渐进渐出平滑过渡的效果。实验结果表明,该成像系统简单可靠,有效地增大了可观测视场,经过拼接处理之后的大视场视频图像清晰度高、实时性强,具有一定的代表性和实用性。     

激光三维彩色人体扫描的数据重建技术

以激光三维扫描仪获得的人体数据的三维彩色数字化过程为例,讨论了删除噪声点、多传感器数据对齐、多传感器数据统一的数据预处理及人体数据重建、网格模型简化、网格平滑和网格细化的三维模型重建算法及特点,给出了人体数据处理实例,最终获得了三维人体模型.并采用直接处理彩色传感器获取的二维彩色图像实现三维彩色数据颜色边界提取方案,得到三维彩色数字化模型.     

On the reconstruction of height functions and terrain maps from dense range data

This paper describes a method for combining multiple, dense range images to create surface reconstructions of height functions. Height functions are a special class of three-dimensional (3-D) surfaces, where one 3-D coordinate is a function of the other two. They are relevant for application domains such as terrain modeling or two-and-half dimensional surface reconstruction. Dense range maps are produced by either a range measuring device combined with a scanning mechanism or a triangulation scheme, such as active or passive stereo. The proposed method follows from a statistical formulation that characterizes the optimal surface estimate as the one that maximizes the posterior probability conditional on the input data and prior information about the application domain. Because the domain of the reconstruction is a two-dimensional (2-D) scalar function, the optimal surface can be expressed as an image, and the variational form of that optimization produces a 2-D partial differential equation (PDE). The PDE consists of two parts: a first-order data term and a second-order smoothing term. Thus optimal surface reconstruction is formulated as the solution to a second-order, nonlinear, PDE on an image, which is related to the family of PDE-based image processing algorithms in the literature. This paper presents the theory for reconstruction and some particular aspects of the numerical implementation. It also analyzes results on both synthetic and real data sets, which show a 75%-95% reduction of the RMS sensor error.     

Adaptive reproducing kernel particle method for extraction of the cortical surface

We propose a novel adaptive approach based on the Reproducing Kernel Particle Method (RKPM) to extract the cortical surfaces of the brain from three-dimensional (3-D) magnetic resonance images (MRIs). To formulate the discrete equations of the deformable model, a flexible particle shape function is employed in the Galerkin approximation of the weak form of the equilibrium equations. The proposed support generation method ensures that support of all particles cover the entire computational domains. The deformable model is adaptively adjusted by dilating the shape function and by inserting or merging particles in the high curvature regions or regions stopped by the target boundary. The shape function of the particle with a dilation parameter is adaptively constructed in response to particle insertion or merging. The proposed method offers flexibility in representing highly convolved structures and in refining the deformable models. Self-intersection of the surface, during evolution, is prevented by tracing backward along gradient descent direction from the crest interface of the distance field, which is computed by fast marching. These operations involve a significant computational cost. The initial model for the deformable surface is simple and requires no prior knowledge of the segmented structure. No specific template is required, e.g., an average cortical surface obtained from many subjects. The extracted cortical surface efficiently localizes the depths of the cerebral sulci, unlike some other active surface approaches that penalize regions of high curvature. Comparisons with manually segmented landmark data are provided to demonstrate the high accuracy of the proposed method. We also compare the proposed method to the finite element method, and to a commonly used cortical surface extraction approach, the CRUISE method. We also show that the independence of the shape functions of the RKPM from the underlying mesh enhances the convergence speed of the deformable model.     

数字全息中利用图像拼接测量大物体的三维形貌

为扩大数字全息的测量视场,使数字全息可以应用于大物体三维形貌的测量,利用菲涅耳离轴数字全息,让照明光依次照明物体的各个区域并分别记录全息图,利用精密电控旋转台精确控制参考光的入射角以保证每次记录时物参角不变,通过参考光入射角的变化量确定物体不同被照明区域之间的位置关系,对获得的物体去包裹的相位图进行拼接,进而得到整个物体的三维形貌.利用该方法测量了大小为11 cm×19 cm的石膏嘴的三维形貌,图像拼接的绝对拼接误差远小于1.14 mm,高度测量误差约为0.5 mm,实验结果说明这种测量方法能够有效地扩大数字全息测量物体三维形貌的视场并且具有和横向分辨率相当的拼接精度.     

A direct multi-volume rendering method aiming at comparisons of 3-Dimages and models

The authors present a new method for direct volume rendering of multiple three-dimensional (3-D) functions using a density emitter model. The work is aimed at obtaining visual assessment of the results of a 3-D image registration algorithm which operates on anisotropic and non-segmented medical data. They first discuss the fundamentals associated with direct, simultaneous rendering of such datasets. Then, they recall the fuzzy classification and fuzzy surface rendering theory within the density emitter model terminology, and propose an extension of standard direct volume rendering that can handle the rendering of two or more 3-D functions; this consists of the definition of merging rules that are applied on emitter clouds. The included rendering applications are related on one hand, to volume-to-volume registration, and on the other hand, to surface-to-volume registration: the first case is concerned with global elastic registration of CT data, and the second one presents fitting of an implicit surface over a CT data subset. In these two medical imaging application cases, the rendering scheme offers a comprehensive appreciation of the relative position of structural information     

Rule-based detection of intrathoracic airway trees

New sensitive and reliable methods for assessing alterations in regional lung structure and function are critically important for the investigation and treatment of pulmonary diseases. Accurate identification of the airway tree will provide an assessment of airway structure and will provide a means by which multiple volumetric images of the lung at the same lung volume over time can be used to assess regional parenchymal changes. The authors describe a novel rule-based method for the segmentation of airway trees from three-dimensional (3-D) sets of computed tomography (CT) images, and its validation. The presented method takes advantage of a priori anatomical knowledge about pulmonary airway and vascular trees and their interrelationships. The method is based on a combination of 3-D seeded region growing that is used to identify large airways, rule-based two-dimensional (2-D) segmentation of individual CT slices to identify probable locations of smaller diameter airways, and merging of airway regions across the 3-D set of slices resulting in a tree-like airway structure. The method was validated in 40 3-mm-thick CT sections from five data sets of canine lungs scanned via electron beam CT in vivo with lung volume held at a constant pressure. The method's performance was compared with that of the conventional 3-D region growing method. The method substantially outperformed an existing conventional approach to airway tree detection.     

Modeling Effects of Random Rough Interface on Power Absorption Between Dielectric and Conductive Medium in 3-D Problem

We study the effects of a random rough surface on the power absorption between a dielectric and conductive medium in a 3-D configuration where the surface height varies in both horizontal directions. The analytic small perturbation method of second order and numerical T-matrix method are used. The absorption depends on the root mean square height, correlation length, and correlation function of the random rough surface. A closed-form expression of power absorption enhancement factor is obtained from small perturbation method of second order. Results show that the T-matrix method agrees with the small perturbation method for rough surfaces with a small slope. We further compare the 3-D results to the previous 2-D results and show significant difference. The power absorption enhancement factor exhibits saturation for the Gaussian correlation function, but not for the exponential correlation function     

Method for three-dimensional data registration from disparate imaging modalities in the NOGA Myocardial Viability Trial

Region-by-region comparison of data concerning left ventricular (LV) status is difficult to perform quantitatively if the data was acquired from disparate imaging modalities. We validated a method for comparing measurements obtained by electromechanical mapping (EMM) catheter with dobutamine stress echocardiography (DSE) via biplane contrast ventriculography, with the assistance of three-dimensional (3-D) echocardiographic data. The ventriculograms were traced and the borders were used to reconstruct the LV in 3-D with the aid of a database of 3-D echocardiographic studies. The 3-D LV was oriented to the EMM data based on the body coordinates and then manually scaled and translated to fit. The EMM data were mapped to the 3-D surface. The 3-D surface was divided into the 16 regions defined for echocardiographic assessment. The mean EMM value for local linear shortening, a parameter of function, was computed in each segment. The EMM and semiquantitative echocardiographic assessments of regional myocardial function were compared by segment, and the volume of the 3-D LV was compared with the volume computed from the ventriculogram. The volume of the 3-D surface correlated closely with that of the ventriculogram (r = 0.97, SEE = 27.4 ml) but with a significant overestimation of 63 +/- 35 ml. There was a highly significant (p < 0.0001) agreement in regional function between EMM and echo. Local linear shortening correlated significantly (p < 0.0001) with echocardiographic severity of wall motion, averaging 9.5 +/- 6.5, 8.1 +/- 5.4, 5.9 +/- 4.8, and 6.2 +/- 3.3 in segments read as normal, hypokinetic, akinetic, and dyskinetic, respectively. The method presented is valid for comparing cardiac parameters derived from disparate image data on a region-by-region basis by employing anatomic landmarks on 3-D reconstructions of the LV endocardial surface.     

Shape from recognition: a novel approach for 3-D face shaperecovery

In this paper, we develop a novel framework for robust recovery of three-dimensional (3-D) surfaces of faces from single images. The underlying principle is shape from recognition, i.e., the idea that pre-recognizing face parts can constrain the space of possible solutions to the image irradiance equation, thus allowing robust recovery of the 3-D structure of a specific part. Parts of faces like nose, lips and eyes are recognized and localized using robust expansion matching filter templates under varying pose and illumination. Specialized backpropagation based neural networks are then employed to recover the 3-D shape of particular face parts. Representation using principal components allows to efficiently encode classes of objects such as nose, lips, etc. The specialized networks are designed and trained to map the principal component coefficients of the part images to another set of principal component coefficients that represent the corresponding 3-D surface shapes. To achieve robustness to viewing conditions, the network is trained with a wide range of illumination and viewing directions. A method for merging recovered 3-D surface regions by minimizing the sum squared error in overlapping areas is also derived. Quantitative analysis of the reconstruction of the surface parts in varying illumination and pose show relatively small errors, indicating that the method is robust and accurate. Several examples showing recovery of the complete face also illustrate the efficacy of the approach.     

Application of DInSAR-GPS Optimization for Derivation of Fine-Scale Surface Motion Maps of Southern California

A method based on random field theory and Gibbs-Markov random fields equivalency within Bayesian statistical framework is used to derive 3-D surface motion maps from sparse global positioning system (GPS) measurements and differential interferometric synthetic aperture radar (DInSAR) interferogram in the southern California region. The minimization of the Gibbs energy function is performed analytically, which is possible in the case when neighboring pixels are considered independent. The problem is well posed and the solution is unique and stable and not biased by the continuity condition. The technique produces a 3-D field containing estimates of surface motion on the spatial scale of the DInSAR image, over a given time period, complete with error estimates. Significant improvement in the accuracy of the vertical component and moderate improvement in the accuracy of the horizontal components of velocity are achieved in comparison with the GPS data alone. The method can be expanded to account for other available data sets, such as additional interferograms, lidar, or leveling data, in order to achieve even higher accuracy