Electromagnetic imaging of buried perfectly conducting cylinder targets using the dynamic differential evolution

Dynamic differential evolution (DDE) for shape reconstruction of perfect conducting cylinder buried in a half‐space is presented. Assume that a conducting cylinder of unknown shape is buried in one half‐space and scatters the field incident from another half‐space where the scattered filed is measured. Based on the boundary condition and the measured scattered field, a set of nonlinear integral equations is derived and the imaging problem is reformulated into an optimization problem. The inverse problem is resolved by an optimization approach, and the global searching scheme DDE is then used to search the parameter space. Numerical results demonstrate that even when the initial guess is far away from the exact one, good reconstruction can be obtained by using DDE both with and without the additive Gaussian noise. © 2011 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2012.     

Comparison of image reconstruction by using near‐field and far‐field data for an imperfect conductor

Image reconstruction by using near‐field and far‐field data for an imperfectly conducting cylinder is investigated. A conducting cylinder of unknown shape and conductivity scatters the incident wave in free space and the scattered near and far fields are measured. By using measured fields, the imaging problem is reformulated into an optimization problem and solved by the genetic algorithm. Numerical results show that the convergence speed and final reconstructed results by using near‐field data are better than those obtained by using far‐field data. This work provides both comparative and quantitative information. © 2001 John Wiley & Sons, Inc. Int J RF and Microwave CAE 11: 69–73, 2001.     

A study of microwave imaging for a metallic cylinder

This article presents the studies of time‐domain inverse scattering for a metallic cylinder which based on the finite‐difference time‐domain (FDTD) method and the dynamic differential evolution (DDE). For this study, the FDTD is used for the analysis of the forward scattering part, while for the DDE is applied for the reconstruction of the two‐dimensional metallic cylinder. For the forward scattering, the FDTD method is used to calculate the scattered E fields. Based on the scattering fields, these inverse scattering problems are transformed into optimization problem. By comparing the simulated scattered fields and the calculated scattered fields, the shape and location of the metallic cylinder are reconstructed. Numerical results demonstrate that, even when the initial guess is far away from the exact one, good reconstruction can be obtained. In addition, the effects of Gaussian noise on the reconstruction results are investigated. © 2012 Wiley Periodicals, Inc. Int J RF and Microwave CAE , 2012.     

Electromagnetic scattered field time series from finite difference time domain trained time delay neural network

This paper uses time delay neural network (TDNN) for predicting electromagnetic (EM) fields scattered from dielectric objects (cylinder, cylinder‐hemisphere, and cylinder‐cone) using: (a) FDTD generated initial field data for similar conducting objects and (b) Statistical information for the nature of fields. Statistical data indicated that the scattered field nature is close to deterministic. The TDNN structure determination uses statistical data for fixing the number of delays and tabular technique to obtain the number of hidden neurons. The TDNN training uses the Levenberg‐Marquardt (LM) algorithm. The model outputs follow standard FDTD results closely.     

Solving time domain microwave imaging for two‐dimensional inhomogeneous dielectric cylinder

This article presents the studies of time domain inverse scattering for a two‐dimensional (2D) inhomogeneous dielectric cylinder buried in a slab medium by the asynchronous particle swarm optimization (APSO) and dynamic differential evolution (DDE) method. The method of finite‐difference time‐domain is employed for the analysis of the forward scattering part, while the inverse scattering problem is transformed into optimization one. The DDE algorithm and the APSO are applied to reconstruct the permittivities distribution of a 2D inhomogeneous dielectric cylinder. Both techniques have been tested in the case of simulated measurements contaminated by additive white Gaussian noise. Numerical results indicate that the APSO algorithm outperforms the DDE in terms of reconstruction accuracy and convergence speed. © 2013 Wiley Periodicals, Inc. Int J RF and Microwave CAE 24:147–154, 2014.     

Efficient preconditioning for image reconstruction with radial basis functions

Radial basis functions are a popular basis for interpolating scattered data during the image reconstruction process in graphic analysis. In this context, the solution of a linear system of equations represents the most time-consuming operation. In this paper an efficient preconditioning technique is proposed to solve these linear systems of equations. This algorithm consists of an iterative method which enforces at each iteration a projection of the residual onto a suitable subspace called coarse space. This constraint is ensured by solving an auxiliary problem at each iteration without regularisation. As increasing the number of the coarse space basis functions increases the computational cost of the algorithm, correct selection of coarse space basis is addressed in the paper. Numerical results illustrate the convergence properties of the proposed method with wavelet-like basis functions and regular distributed radial basis functions for image reconstruction.     

Electromagnetic imaging for shape and variable conductivity

We consider the inverse problem of determining both the shape and the conductivity of a two-dimensional (2D) conducting scatterer from the knowledge of the far-field pattern of TM waves by solving the ill-posed nonlinear equation. Based on the boundary condition and measured scattered field, a set of nonlinear integral equations is derived and the imaging problem is reformulated into an optimization problem. Satisfactory reconstructions are achieved by the genetic algorithm. Numerical results demonstrate that, even when the initial guess is far away from the exact one, good reconstruction can be obtained. In addition, the effect of Gaussian noise on the reconstruction results is investigated. The numerical results show that multiple incident directions permit good reconstruction of shape and, to a lesser extent, conductivity in the presence of noise in measured data. © 2004 Wiley Periodicals, Inc. Int J RF and Microwave CAE 14, 433–440, 2004.     

小波高频子带变换裁剪阈值SAMP算法研究

文中首先针对离散小波变换（ DWT）破坏了低频逼近系数之间的相关性,导致重构质量变差的问题,提出小波高频子带变换（ HFSBWT）的稀疏表示方法。其次针对稀疏度自适应匹配追踪（ SAMP）算法的原子候选集在每次迭代时成倍增加造成存储空间浪费和重构时间变长等问题,提出裁剪阈值稀疏度自适应匹配追踪（ CTSAMP）算法。最后仿真结果表明：对于同一重构算法,小波高频子带变换的图像重构峰值信噪比提高3 dB左右。在小波高频子带变换稀疏表示后采用裁剪阈值稀疏度自适应匹配追踪算法,重构图像的性能有了明显的提高,重构时间缩短一半。     

Radiation characteristics of strip‐loaded dielectric‐coated conducting cylinder

The radiation characteristics of strip‐loaded dielectric‐coated conducting cylinder are investigated theoretically for the infinite and finite periodic structures. For the infinite case, the strip electric current expansion satisfying edge condition and the field expression with a summation of space harmonics are applied to solve a homogeneous matrix equation. The integral equation is derived for the finite structure by using the inverse Fourier transform and the strip current expansion. The influences of the strip width, cylinder radius, and finite strip number on the radiation characteristics (leakage constant, phase constant, radiation pattern, and beam scanning) are investigated. The results of the finite periodic strips are compared with those of the infinite extent structure and good agreement is found. © 2007 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2008.     

Frequency Domain Frequency Shift for Optimal Filtering of Cyclostationary Signals

Parker, G., Frequency Domain Frequency Shift for Optimal Filtering of Cyclostationary Signals, Digital Signal Processing12 (2002) 561–589Optimum reconstruction of corrupted cyclostationary signals is achieved using the filter class known as the frequency shift filter. This filter requires the received signal to be shifted by the frequencies of cyclostationarity of the signal and with a frequency domain implementation it will often be best to effect the frequency shifts directly in the frequency domain. This paper introduces techniques for exactly achieving these shifts as well as providing more computationally efficient approximate solutions.     

散乱数据拟合的自适应分片逆尺度空间算法

散乱数据拟合(逼近)是在信号处理、计算机图形学等领域中被广泛研究的问题, 近些年,利用优化方法获得散乱数据的稀疏表示逼近解也成为了优化和曲面重构交叉领域的热 点。基于由B 样条生成的PSI 空间中的散乱点曲面拟合问题和分片稀疏的联系,将分片稀疏性 引入到Bregman 逆尺度空间算法(ISS)中,提出一种自适应的分片逆尺度空间(aP_ISS)算法,处 理散乱数据的曲面拟合问题。通过对逆尺度空间系统分片符号一致性分析,得到了自适应分片 逆尺度空间系统的性能保证定理和避免了aP_ISS 参数的选取。应用到散乱点曲面重构问题上 的数值实验结果表明,该算法不仅可以有效拟合曲面,还能够较好保护分片稀疏性。     

Linear Image Reconstruction by Sobolev Norms on the Bounded Domain

The reconstruction problem is usually formulated as a variational problem in which one searches for that image that minimizes a so called prior (image model) while insisting on certain image features to be preserved. When the prior can be described by a norm induced by some inner product on a Hilbert space, the exact solution to the variational problem can be found by orthogonal projection. In previous work we considered the image as compactly supported in and we used Sobolev norms on the unbounded domain including a smoothing parameter γ>0 to tune the smoothness of the reconstructed image. Due to the assumption of compact support of the original image, components of the reconstructed image near the image boundary are too much penalized. Therefore, in this work we minimize Sobolev norms only on the actual image domain, yielding much better reconstructions (especially for γ≫0). As an example we apply our method to the reconstruction of singular points that are present in the scale space representation of an image.     

Implementation of PEC boundary condition for Laguerre‐RPIM meshless method with novel uniform nodal distribution

The implementation of perfect electric conductor (PEC) boundary condition for meshless radial point interpolation method (RPIM) with the weighted decaying Laguerre polynomial (WLP) is investigated. A novel uniform nodal placement is proposed and the number of H‐nodes reduces to about a half of that for the conventional scheme. There are only E‐nodes scattered on the PEC boundary. The E‐node and H‐node have the same scale of support domain nodes. The image theory is adopted to update the implicit electric equations on the PEC boundary. This scheme is also suitable for nonuniform node distribution. Numerical results have verified the accuracy of the proposed method.     

The curvature interpolation method for surface reconstruction for geospatial point cloud data

ABSTRACT

Surface reconstruction for scattered data is an ill-posed problem and most computational algorithms become overly expensive as the number of sample points increases. This article studies an effective partial differential equation (PDE)-based algorithm, called the curvature interpolation method with iterative refinement (IR-CIM). The new method iteratively utilizes curvature-related information which is estimated from an intermediate surface of the nonuniform data and plays a role of driving force for the reconstruction of a reliable image surface. The IR-CIM is applied for digital elevation modelling for geospatial point cloud data of overlapping strip scans acquired by light detection and ranging (LiDAR) technology. This article also introduces an effective initialization strategy for large areas of missing data and a robust method for the elimination of the Moiré effect over strip overlaps. The resulting algorithm converges to a piecewise smooth image, with little dependence on sample rates, outperforming inverse-distance weighting methods in both efficiency and accuracy.     

基于自适应权值的点云三维物体重建算法研究

基于三维扫描点云数据的三维物体重建是计算机图形学中非常重要的课题,在计 算机动画、医学图像处理等多方面都有应用。其中基于最小二乘问题的Levenberg-Marquart 算 法和基于极大似然估计的M-Estimator 算法都是不错的方案。但是当点的数量过多过少或者点 云中有噪声时,这些方案产生的结果都会有较大的误差,影响重建的效果。为了解决这两个问 题,结合Levenberg-Marquart 算法和M-Estimator 算法,提出了一种新的算法。该算法结合 Levenberg-Marquart 算法较快的收敛性和M-Estimator 算法的抗噪性,能很好地解决点数量较多 和噪声点影响结果的问题。通过在M-Estimator 的权重函数上进行改进,提出自适应的权值函 数,用灵活变动和自适应的值代替原来的固定值,使算法在噪声等级较高时也能表现良好。最 后将算法应用在球体和圆柱上,并和最新的研究成果进行对比,数据说明算法无论是在点云数 量较多还是在噪声等级较高的情况下都明显优于其他已知算法。     

Perturbation‐resilient block‐iterative projection methods with application to image reconstruction from projections

A block‐iterative projection algorithm for solving the consistent convex feasibility problem in a finite‐dimensional Euclidean space that is resilient to bounded and summable perturbations (in the sense that convergence to a feasible point is retained even if such perturbations are introduced in each iterative step of the algorithm) is proposed. This resilience can be used to steer the iterative process towards a feasible point that is superior in the sense of some functional on the points in the Euclidean space having a small value. The potential usefulness of this is illustrated in image reconstruction from projections, using both total variation and negative entropy as the functional.     

Line Localization from Single Catadioptric Images

Indoor environments often contain several line segments. The 3D reconstruction of such environments can thus be reduced to the localization of lines in the 3D space. Multi-view reconstruction requires the solution of the correspondence problem. The use of a single image to localize space lines is attractive, since the correspondence problem can be avoided. However, using a central camera the line localization from single image is an ill-posed problem, because there are infinitely many lines sharing the same image.     

基于Kinect的深度数据融合方法

与传统三维激光扫描仪相比, Kinect作为一种新型深度相机, 具有价格低廉、深度数据获取能力强、RGB影像与深度影像同步获取等优势, 然而面对较大室内场景精细建模却存在数据量大、建模范围有限、对硬件环境依赖性强等问题。因此, 在现有单一模型建模基础上, 提出了基于Kinect深度影像的多模型数据融合方法, 实现模型间的自动拼接。最后通过两组实验对提出的数据融合方法进行了验证, 并取得了较好的模型拼接效果。     

基于Shearlet变换和多尺度Retinex的遥感图像增强算法

传统的小波变换、曲波变换和轮廓波变换无法对图像提供最优的稀疏表示,不能取得好的增强效果,为此,提出了一种基于剪切波(Shearlet)变换的图像增强算法.经Shearlet变换,图像被分解成低频分量和高频分量.首先,对Shearlet变换分解后的低频分量进行多尺度Retinex(MSR)调整,以减轻光照条件对图像的影响;其次,对各尺度、各方向上的高频系数采用阈值抑噪来消除噪声;最后,对重构图像进行模糊对比度增强,提高图像的整体对比度.实验结果表明该算法能够明显改善图像的视觉效果,突出图像的纹理细节且具有良好的抗噪性能.与直方图均衡(HE)、MSR、基于非下采样轮廓波变换(NSCT)的图像模糊增强(NSCT_fuzzy)算法相比,图像清晰度、信息熵、峰值信噪比(PSNR)均有一定的提高,且运行时间缩短为MSR的1/2和NSCT_fuzzy的1/10左右.     

基于康普顿散射的能谱数据重建电子密度图像

提出一种基于能谱和行扫描的康普顿散射成像方法。该方法通过逐行扫描，把一个较大的图像重建问题分解成几个独立的小而容易解决的问题进行重建。对于正向方程中源于非扫描行的衰减作用，利用已重建行的像素值来计算；对源于扫描行自身的衰减作用，用逐步近似(SAP)的方法来计算。为了减小说差在不同扫描行之间的传播，利用途射数据对重建结果进行校正。实验证明，该方法速度快、可靠性高，易于实现。