一种新的频谱分析图像重建算法及模拟

这种频谱分析图像重建算法利用二维傅里叶级数的各正交基函数的投影向量,去逼近图像 函数的投影向量,利用优化准则,得到各正交基函数的权系数,再经过傅里叶反变换,即可重建出原始的图像函数。计算机模拟表明,该算法重建时间不足1秒,选择合适的近似级数,对复杂场的图像重建,也能使最大误差不超过5%,平均误差不超过1%。     

声学重建圆形温度场中区域分块的研究

为完善极少声波飞行时间测量数据下温度场的实时在线监测,提出将重建精度高的指数SVD法应用于圆形区域,着重研究了更多区域划分块数对重建温度场精度的影响。首先按一定方式将待测温度场划分成若干区域,逐渐增加分块数目至545块(继续增加将影响监测实时性)。然后分别对单峰、双峰温度场模型采用指数SVD法实现温度场重建,利用均方根误差评价重建精度。重建结果表明,某些条件一定时,分块数目逐渐增加,重建精度有所提高。     

基于哈特曼波前探测的流场层析重建系统仿真

基于哈特曼波前探测的流场层析重建技术结合了光学波前探测技术和计算机层析技术。重建系统由哈特曼传感器探测平行光束穿过流场后的投影波前,采用计算机层析技术重建流场物理量的空间分布。在介绍哈特曼流场层析重建原理的基础上,对流场重建的整个过程进行了计算机仿真,重建的RMS误差为0.0726。结果表明,该技术可以很好地实现流场的层析重建,在材料、流场研究等工程实际测量中具有良好的应用前景。     

一种基于模型的光学层析图像重建方法

光学层析图像重建是个病态问题,测量误差会在重建过程中被放大,对此,提出一种以广义高斯马尔可夫随机场模型为先验信息的光学层析图像重建方法.重建过程是对目标函数的优化过程,目标函数关于光学参数的梯度计算是算法中的难点,因此,提出一种基于梯度树的梯度计算方法.文中分别给出了吸收系数和散射系数的重建结果,并引入三个指标因子衡量重建图像的质量,进而列出不同重建算法下,重建图像的指标值.最后通过对重建结果和指标因子取值的比较,分析基于模型的重建算法的有效性.     

强偏折场的光偏折层析重建技术

强偏折场的重建是光学层析技术测量复杂流场领域的难点问题.在研究现有重建算法及其适用性的基础上,结合光线追迹算法提出基于曲线路径反演的正则化修正重建技术.该技术克服了现有重建技术中光路直进的假设,基于几何光学原理设计了光线通过强偏折场的积分路径追踪算法,使用代数重建技术和正则化重建技术相结合的思想,通过偏折角投影数据的迭代修正实现非线性反演.使用该技术对强偏折场进行数值重建,证实了其在有限角投影数据条件下重建大梯度折射率分布的有效性,并显示了其在刻画场关键特性方面相对于现有算法的优势.     

利用字典学习的浅海被动声层析

针对被动海洋声层析,提出了一种利用字典学习从海洋环境噪声反演浅海声速剖面的方法。首先,通过海洋噪声互相关函数提取出两个水平阵列间的经验格林函数;其次,通过字典学习从数据生成字典矩阵来稀疏表征声速剖面;最后通过搜索稀疏的系数来实现对浅海声速剖面的反演。通过南海实验数据对本方法进行了验证,相对于传统被动海洋声层析方法实际反演结果的均方根误差降低为0.53 m·s^-1。而且搜索参数更少,同时具有较高的准确性。     

基于自适应投影增强的压缩感知CT图像重建

针对投影数据受噪声影响严重、被检测工件体积大获取投影数据不完全等导致重建质量差的问题,提出一种自适应反锐化掩模算法对某发动机模拟件投影数据均匀抽取60个角度投影进行预处理,根据其边缘信息设定阈值进行自适应去噪并对高频信息乘以自适应增益增强,采用TV最小化约束的代数重建(ART)算法重建.将改进算法与经典ART、经典反锐化掩模技术处理投影以及投影未处理的POCS-TVM算法进行对比分析,实验结果表明,该方法能够平滑噪声,提高对比度,进而提升不完全投影重建图像质量.重建同样大小的图像,相对于全角度投影迭代一次时间100 s, 60个角度投影迭代一次18.7 s,时间缩短近6倍,大量节省重建时间.     

基于极坐标的扇束CT周期性优化算法

为了提高传统扇束计算机断层扫描(Computed Tomography,CT)卷积反投影重建算法(Conventional Back-Projection,CBP)的重建速度,提出了一种快速的扇束CT重建算法.该算法结合极坐标特性,利用三角函数一定程度上的周期性,对传统CBP重建算法进行了改进,减少了正余弦函数的计算量和重建所需要的外围循环次数.同样利用该特性对极坐标重建后的图像坐标转换过程进行改善,从而对CBP算法进行了改进,降低了重建时间.     

基于视差空间运动估计的高精度立体视觉定位

立体视觉定位算法的运动估计通常在3D欧式空间中进行,但由于特征点3D坐标的噪声各向异性且分布不均匀,3D重建在深度方向上比另两个方向上的准确性差,从而导致3D欧式空间运动估计精确不高.本文提出了一种新的基于视差空间运动估计的高精度立体视觉定位算法.算法首先采用视差空间4点闭环线性解法和RANSAC算法得到初始鲁棒运动估计和匹配内点.接着,利用新的视差空间再投影误差函数提出了基于LM算法的视差空间运动参数非线性优化方法,对初始运动参数进一步优化.视差空间噪声分布均匀且各向同性,本文的初始运动参数线性估计和非线性优化都在视差空间中进行且能达到全局最小.仿真实验和真实实验结果表明,本文算法能得到高精度的立体视觉定位结果,优于传统的3D欧式空间运动估计方法.     

组合步长的改进仿射投影主动噪声控制算法

为了改善在主动噪声控制(Active Noise Control,ANC)中由不平稳脉冲噪声引起的经典仿射投影算法稳态误差高的缺陷,利用鲁棒类M估计器代价函数对误差信号的饱和特性,将其与权重向量的L2范数约束相结合,提出类M估计器函数仿射投影算法。该算法的收敛精度相较于经典符号仿射投影算法提升3.2 dB。为了进一步提升收敛速度,将组合步长技术引入上述算法来自适应调节权重约束中的步长参数,调节收敛速度与稳态误差之间的矛盾。仿真结果表明,最终提出的算法突破固定步长的限制,可实现更快的收敛速率和更低的稳态误差,相较于已有仿射投影算法,在收敛速度方面提升2倍,在收敛精度方面提高10 d B。该算法可为之后仿射投影算法的研究提供理论指导和实验依据。     

基于三视图的实体重建技术研究

基于三视图的三维实体重建技术是根据已有二维视图中的几何信息和拓扑信息,生成相应的三维实体模型。以AutoCAD绘制的三视图及DXF格式的文件信息为基础,提出并实现了一种由三视图重建三维实体的算法。通过对三视图的规则处理,由计算机自动实现实体重建,对三视图分别进行平移、旋转、拉伸操作,然后作相应的布尔运算即可反求出该视图所对应的三维实体。     

Comparative study on basis functions for projection matrix of three-dimensional tomographic reconstruction for analysis of dropletbehavior from electrohydrodynamic jet

Three-dimensional optical tomography techniques were developed to reconstruct three-dimensional objects using a set of two-dimensional projection images. Five basis functions, such as cubic B-spline, o-Moms, keys, and cosine functions and Gaussian basis functions, were used to calculate the weighting coefficients for a projection matrix. Two different forms of a multiplicative algebraic reconstruction technique were also used to solve inverse problems. The reconstruction algorithm was examined by using several phantoms, which included droplet behaviors and random distributions of particles in a volume. The three-dimensional volume comprised of particles was reconstructed from four projection angles, which were positioned at an offset angle of 45° between each other. Then, three-dimensional velocity fields were obtained from the reconstructed particle volume by three-dimensional cross correlation. The velocity field of the synthetic vortex flow was reconstructed to analyze the three-dimensional tomography algorithm.     

Orthographic double-beam holographic interferometry for limited-view optical tomography

A simultaneous algebraic reconstruction technique (SART) that was first applied to limited-view optical tomography reconstruction of a three-dimensional asymmetric refractive-index field or a temperature distribution is presented and numerically simulated. Within two orthographic-view directions and limited view ranges, the reconstruction speed and accuracy of the SART are adequate. A new orthographic double-beam holographic-interferometric system from which multidirectional interferometric data can be obtained is first built. An asymmetric heat air-flow field is experimentally investigated by the use of orthographic double-beam holographic interferometry with double exposures. The temperatures reconstructed with the SART are consistent with those measured with a thermocouple.     

Sparse‐view statistical iterative head CT image reconstruction via joint regularization

It is a significant challenge to accurately reconstruct medical computed tomography (CT) images with important details and features. Reconstructed images always suffer from noise and artifact pollution because the acquired projection data may be insufficient or undersampled. In reality, some “isolated noise points” (similar to impulse noise) always exist in low‐dose CT projection measurements. Statistical iterative reconstruction (SIR) methods have shown greater potential to significantly reduce quantum noise but still maintain the image quality of reconstructions than the conventional filtered back‐projection (FBP) reconstruction algorithm. Although the typical total variation‐based SIR algorithms can obtain reconstructed images of relatively good quality, noticeable patchy artifacts are still unavoidable. To address such problems as impulse‐noise pollution and patchy‐artifact pollution, this work, for the first time, proposes a joint regularization constrained SIR algorithm for sparse‐view CT image reconstruction, named “SIR‐JR” for simplicity. The new joint regularization consists of two components: total generalized variation, which could process images with many directional features and yield high‐order smoothness, and the neighborhood median prior, which is a powerful filtering tool for impulse noise. Subsequently, a new alternating iterative algorithm is utilized to solve the objective function. Experiments on different head phantoms show that the obtained reconstruction images are of superior quality and that the presented method is feasible and effective.     

平行线束法的仿射研究

用 3 个仿射图的投射方向构成 1 个仿射坐标系,同时也构成 1 个三棱锥,在此仿射坐标系中用球面三角重新研究由两个仿射图求第 3 个仿射图的投影作图理论 ——平行线束法。进一步还给出了由两个仿射图得到正投影的条件、由两个正投影得到第 3 个正投影的条件、以及由 V,H 两投影得到指定方向上的正投影的条件,简化了研究过程,得到了更简单的公式。     

Discrete cosine transform-based shift estimation for fringe pattern profilometry using a generalized analysis model

What is believed to be a new analysis algorithm to carry out profile measurement with low computational complexity and less noise sensitivity is presented. First, a discrete cosine transform (DCT)-based representation method is introduced to express the height distribution of a 3D surface. Then a novel shift estimation algorithm, called the DCT-based shift estimation (DCT-SE), is presented to reconstruct 3D object surfaces by using the proposed expression and the generalized analysis model. The advantage of DCT-SE is that without loss of measurement precision it provides lower computational complexity to implement 3D reconstruction from nonlinearly distorted fringe patterns and, at the same time, survives the random noise. Simulations and experiments show that the proposed DCT-SE is a fast, accurate, and efficient reconstruction algorithm for digital projection- based fringe pattern profilometry techniques.     

波尔克定理的计算机化

计算机图学中轴测变换的典型算法是旋转加投影。方法可行,但有旋转角与轴测效果关系不够简明和正、斜轴测得分开讨论的两点不足。本文用图解法推出波尔克定理及轴测投射方向的表达式,使计算机图学中的轴测变换及自动消隐获得一种直观、简洁的算法,并给出本算法的BASIC子程序。     

Denoising multicriterion iterative reconstruction in emission spectral tomography

In the study of optical testing, the computed tomogaphy technique has been widely adopted to reconstruct three-dimensional distributions of physical parameters of various kinds of fluid fields, such as flame, plasma, etc. In most cases, projection data are often stained by noise due to environmental disturbance, instrumental inaccuracy, and other random interruptions. To improve the reconstruction performance in noisy cases, an algorithm that combines a self-adaptive prefiltering denoising approach (SPDA) with a multicriterion iterative reconstruction (MCIR) is proposed and studied. First, the level of noise is approximately estimated with a frequency domain statistical method. Then the cutoff frequency of a Butterworth low-pass filter was established based on the evaluated noise energy. After the SPDA processing, the MCIR algorithm was adopted for limited-view optical computed tomography reconstruction. Simulated reconstruction of two test phantoms and a flame emission spectral tomography experiment were employed to evaluate the performance of SPDA-MCIR in noisy cases. Comparison with some traditional methods and experiment results showed that the SPDA-MCIR combination had obvious improvement in the case of noisy data reconstructions.     

离散余弦小波包变换及语音信号压缩感知

针对语音信号压缩感知问题,在研究语音离散余弦变换(Discrete Cosine Transform,DCT)系数和小波包变换(Wavelet Packet Transform,WPT)特性的基础上构造了离散余弦小波包变换(Discrete Cosine Wavelet Packet Transform,DCWPT)。DCWPT首先获取语音信号的DCT域系数,结合语音频谱特性选取部分DCT系数进行WPT变换,从而得到比DCT系数更加稀疏的DCWPT系数。为将此变换直接用于压缩感知,构造了DCWPT的正交稀疏分解矩阵并分析了其稀疏表示性能。结合稀疏表示基优化了正交匹配追踪重构算法,提出了基于DCWPT的语音信号压缩感知框架。通过压缩重构对照实验,采用主客观评价指标,得出该方法优于传统基于DCT的语音压缩感知方法的结论。