基于子孔径分解的SAR动目标检测方法

 运动目标在合成孔径雷达SAR(Synthetic Aperture Radar)图像中的成像会出现模糊,散焦等现象,并且会在方位向出现明显的偏移,这些会导致运动目标的目标杂波比TCR(Target-to-clutter Ratio)降低.本文在子孔径分解技术的基础上提出一种从单通道SAR单视复图像SLC(Single Look Complex)中检测动目标的方法,该方法通过子孔径图像之间的相减操作来抑制杂波,从而提高TCR.通过对机载CV-580数据和星载Envisat ASAR 数据进行测试,证明了该方法的有效性.     

Geometry-adapted hexahedral meshes improve accuracy of finite-element-method-based EEG source analysis

Mesh generation in finite-element- (FE) method-based electroencephalography (EEG) source analysis generally influences greatly the accuracy of the results. It is thus important to determine a meshing strategy well adopted to achieve both acceptable accuracy for potential distributions and reasonable computation times and memory usage. In this paper, we propose to achieve this goal by smoothing regular hexahedral finite elements at material interfaces using a node-shift approach. We first present the underlying theory for two different techniques for modeling a current dipole in FE volume conductors, a subtraction and a direct potential method. We then evaluate regular and smoothed elements in a four-layer sphere model for both potential approaches and compare their accuracy. We finally compute and visualize potential distributions for a tangentially and a radially oriented source in the somatosensory cortex in regular and geometry-adapted three-compartment hexahedra FE volume conductor models of the human head using both the subtraction and the direct potential method. On the average, node-shifting reduces both topography and magnitude errors by more than a factor of 2 for tangential and 1.5 for radial sources for both potential approaches. Nevertheless, node-shifting has to be carried out with caution for sources located within or close to irregular hexahedra, because especially for the subtraction method extreme deformations might lead to larger overall errors. With regard to realistic volume conductor modeling, node-shifted hexahedra should thus be used for the skin and skull compartments while we would not recommend deforming elements at the grey and white matter surfaces.     

Computed masks in coronary subtraction imaging

In this paper we propose a method to overcome the effects of cardiac and respiratory motion in coronary subtraction imaging. We present the ideas of retrospective gating of masks, where both cardiac and respiratory phases are measured for a set of masks, and are subsequently used in a functional decomposition of motion. Through retrospective gating of masks, we are able to select appropriate images and to perform temporal and spatial processing on them to produce computed masks, subtraction of which should lead to motion-artifact-free images. The computed masks are built from two components: the first includes the time-variant structures related to respiration, such as ribs and soft tissues of the chest wall, and the second incorporates the time-variant structures related to cardiac motion. A preliminary study of the method in the area of digital subtraction angiography produced images which are comparable to but not better than those produced by techniques in current clinical practice: we discuss the reasons for this.     

Throughput analysis of a CSMA based WLAN with successive interference cancellation under Rayleigh fading and shadowing

In this paper, we consider a carrier sense multiple access based wireless local area network (WLAN) with a successive interference cancellation (SIC) technique. We develop an analytical model to compute the average throughput of a user in a WLAN with the SIC technique in presence of path loss, Rayleigh fading and log-normal shadowing. We then validate the model via simulation. By means of the developed analytical model, we compute the average throughput of a user in WLAN systems without and with the SIC technique and evaluate the throughput gain provided by the SIC technique. We find that the throughput gain provided by the SIC technique is significant. However, the throughput gain varies significantly depending on the parameters of network and wireless channel. We find that the throughput gain provided by the SIC technique increases with increasing the number of users in WLAN, medium access rate of the users and the variance in shadowing and it decreases with increasing the data transmission rate. We also investigate the effect of the decoding capability of the SIC technique on the throughput performance. We find that throughputs obtained with decoding capability of 2 and 3 packets are very close.     

Three-dimensional digital subtraction angiography

A dye-edge tracking algorithm was used to determine the corresponding points in the two images (anterior-posterior and lateral) of the digital subtraction biplane angiography. This correspondence was used to reconstruct three-dimensional images of cerebral arteries in a dog experiment and a clinical observation. The method was tested by comparing the measured image of oblique view to the computed reconstructed image. For the present study, we have developed three new algorithms. The first algorithm is to determine the corresponding dye-edge points using the fact that the density of contrast media at the moving edge shows the same changing pattern in the two projection views. This moving pattern of dye-edge density is computed using a matching method of cross correlation for the two sequential frames' dye density. The second algorithm is for simplified perspective transformation, and the third is to identify the corresponding points using a complementary method for locating the approximate points on the small vessels. The present method can be applied to compute the velocity of blood flow using the dye-edge displacement and the three-dimensional distance data.     

Decomposition-Based Recursive Least Squares Algorithm for Wiener Nonlinear Feedback FIR-MA Systems Using the Filtering Theory

A decomposition-based recursive least squares algorithm is developed for Wiener nonlinear systems described by finite impulse response moving average models. After transferring a finite impulse response moving average (FIR-MA) model to a controlled autoregressive model, we compute the parameters by combining the decomposition principle and the least squares method and using the filtering idea. The simulation results validate the proposed algorithm.     

Elastic registration of fMRI data using Bézier-spline transformations

A three-dimensional (3-D) elastic registration algorithm has been developed to find a veridical transformation that maps activation patterns from functional magnetic resonance imaging (fMRI) experiments onto a 3-D high-resolution anatomical dataset. The proposed algorithm uses trilinear Bézier-splines and a 3-D voxel-based optimization technique to determine the transformation that maps the functional data onto the coordinate system of the anatomical dataset. Simple conditions are presented which guarantee that the data are mapped one-to-one on each other. Two voxel-based similarity measures, the linear correlation coefficient and the entropy correlation coefficient, are used. Their performance with respect to the registration of fMRI data is compared. Tests on simulated and real data have been performed to evaluate the accuracy of the method. Our results demonstrate that subvoxel accuracy can be achieved even for noisy low-resolution multislice datasets with local distortions up to 10 mm. Although the method is optimized for the registration of functional and anatomical MR images, it can also be used for solving other elastic registration problems.     

一种有效的图像阴影自动去除算法

目标跟踪与检测研究中,在检测运动前景时也会检测到运动目标投射的阴影。阴影使得运动目标发生几何变形,可能造成运动目标粘连,甚至造成检测不到目标。阴影去除后才能较真实的得到运动目标重心。本文研究一种利用图像YCbCr颜色信息去除阴影的方法。首先利用背景减的方法得到带影子的目标区域,其次进行YCbCr空间的背景减,由于影子和目标物体在YCbCr空间背景减信息有较大差别,因此可以通过阈值判断得到去影之后的精确目标区域,目标物体识别的精确性和鲁棒性将会得到提高。实验结果表明,该方法在去除阴影的同时又较好地保留了前景目标的信息,是一种有效的阴影去除方法。      

惯导系统航迹误差与真航向误差相关性研究

为了寻找一种新的评定飞行试验中真航向精度的方法,文中采用全球定位系统(GPS)作为参考基准,以两套不同型号的惯导系统作为试验对象,通过飞行试验研究惯导系统航迹误差与真航向误差的相关性。试验数据及分析结果表明,采用航迹误差间接评定真航向精度是可信的。     

用于交通监视的视频感兴趣区域提取方法

提出了一种基于并行架构的感兴趣区域提取方法.该方法先采用基于像素色度归类的背景差法定位运动区域,同时利用监视画面的亮度和色度信息提取车牌可能区域;然后将二者的结果进行综合实现车牌区域提取.仿真实验表明,该方法筒捷,计算量小,便于用FPGA和DSP快速实现.     

Motion detection in moving camera videos using background modeling and FlowNet

Real-time moving object detection is challenging for moving cameras due to the moving background. Many studies use homography matrix to compensate for global motion by warping the background model to the current frame. Then, the pixel difference between the current frame and the background model is used for background subtraction. Moving pixels are extracted by applying adaptive threshold and some post-processing techniques. On the other hand, deep learning-based dense optical flow can be efficient enough to extract the moving pixels, but it increases computational cost. This study proposes a method to enhance a classical background modeling method with deep learning-based dense optical flow. The main contribution of this paper is to propose a fusing algorithm for dense optical flow and background modeling approach. The background modeling methods are error-prone, especially with continuous camera movement, while the optical flow method alone may not always be efficient. Our hybrid method fuses both techniques to improve the detection accuracy. We propose a software architecture to run background modeling and dense optical flow methods in parallel processes. The proposed implementation approach significantly increases the method’s working speed, while the proposed fusion and combining strategy improve detection results. The experimental results show that the proposed method can run at high speed and has satisfying performance against the methods in the literature.     

用功率谱相减的圆谐联合小波变换相关器作多目标检测

将小波变换与圆谐联合变换相关器相结合,应用功率谱相减技术进行多目标检测,可以从输出面上直接看出系统对真目标的旋转不变检测及识别假目标的能力。分析和量化了输入景物噪声对结果的影响。计算机模拟实验表明这种方法明显改善了普通圆谐联合变换相关器的性能,具有良好的相关输出性能和抗噪声能力。     

Improved wavelength decomposition approach for computing blocking probabilities in WRONs

Wavelength decomposition approach has been proposed to compute blocking probability (BP) of fixed routing in wavelength-routed optical networks (WRONs) without wavelength conversions.By means of wavele...     

Two-layer mesh network optimization based on inter-layer decomposition

Presently, backbone data networks are converging toward a typical two-layer architecture of an IP/MPLS layer over an optical layer. In this paper, we study the problem of maximizing a utility function for an Internet service provider (ISP) of a two-layer mesh networks and propose an efficient decomposition method based on Lagrange relaxation. Differing from previous works on two-layer mesh networks, our proposed decomposition method decomposes an original two-layer mathematic optimization problem, respectively, into an IP/MPLS-layer and an optical-layer optimization problem by slacking the constraints between the two layers. This decomposition method enables to control the trade-off between running time and quality of the feasible solution. Numerical results for a variety of networks indicate that our proposed decomposition method is attractive to quickly find near optimal solutions.     

Accurate Image Rotation Using Hermite Expansions

In this paper, we propose an approach for the accurate rotation of a digital image using Hermite expansions. This exploits the fact that if a 2-D continuous bandlimited Hermite expansion is rotated, the resulting function can be expressed as a Hermite expansion with the same bandlimit. Furthermore, the Hermite coefficients of the initial 2-D expansion and the rotated expansion are mapped through an invertible linear relationship. Two efficient methods to compute the mapping between Hermite coefficients during rotation are proposed. We also propose a method for connecting the Hermite expansion and a discrete image. Using this method, we can obtain the Hermite expansion from a discrete image and vice versa. Combining these techniques, we propose new methods for the rotation of discrete images. We assess the accuracy of our methods and compare them with an existing FFT-based method implementing three shears. We find that the method proposed here consistently has better accuracy than the FFT-based method.      

基于特征点的多运动目标跟踪

该文针对智能监控的需求,提出基于特征的多运动目标跟踪算法。通过自适应Marr小波核函数背景建模算法,在冗余离散小波域进行多运动目标识别。运动跟踪采用SIFT特征粒子滤波算法,并采用队列链表法记录多运动目标之间的数据关联,在提高识别准确率的同时降低了运算的复杂度。实际测试表明,该算法对于多运动目标识别跟踪具有更优越的实时性和抗遮挡性,在智能监控领域具有较广泛的应用前景。     

Estimating the 3D skeletons and transverse areas of coronary arteries from biplane angiograms

A method for estimating the three-dimensional (3D) skeletons and transverse areas of the lumens of coronary arteries from digital X-ray angiograms is described. The method is based on the use of a 3D generalized cylinder (GC) consisting of a series of 3D elliptical disks transverse to and centered on a 3D skeleton (medial axis) of the coronary arteries. The estimates of the transverse areas are based on a nonlinear least-squares-error estimation technique described by D.W. Marquardt (1963). This method exploits densitometric profiles, boundary estimates, and the orientation of the arterial skeleton in 3-space and includes an automatic artery tracking procedure. It applies an adaptive window to the densitometric profile data that are used in the parameter estimation. Preliminary experimental tests of the procedure on angiograms of in vivo human coronaries and on synthetic images yield encouraging results.     

激光辐照树脂基复合材料的一维温度场模拟

为了解决激光辐照树脂基复合材料时热解热和移动热解面给温度场求解带来的难题,通过修正处理相变问题的热焓法,建立了连续激光辐照树脂基复合材料的一维温度场模型,简化了求解过程。在此基础上采用“历史最高温度点追踪法”对热焓法模型进行了进一步修正,使之能够解决脉冲激光辐照复合材料时温度双向变化与热解过程不可逆之间的矛盾,从而对脉冲激光辐照的情况也能适用。用有限差分方法进行离散后,编写了FORTRAN程序求得数值解。计算结果与实验结果基本相符,最后模型分析了脉冲激光参量对树脂基复合材料温升的影响。     

Repeatable and Realistic Experimentation in Mobile Wireless Networks

Experimenting with mobile and wireless networks is challenging because testbeds lack repeatability and existing simulation models are unrealistic for real-world settings. We present practical models for the physical and MAC layer behavior in mobile wireless networks in order to address this challenge. Our models use measurements of a real network rather than abstract radio propagation and mobility models as the basis for accuracy in complex environments. We develop an adaptive measurement technique in order to maximize the accuracy of our models in dynamic environments. The models then predict the packet delivery, deferring, and collision probability in the same network for an arbitrary set of transmitters. This allows to explore the performance of different network and higher layer protocols in simulation or emulation under identical and realistic conditions. We evaluate the accuracy of our models empirically by comparing them to benchmark measurements. We find that our models are effective at reproducing mobile scenarios in various environments. Across many experiments in realistic environments, we are able to reproduce link delivery probabilities with RMS error below 12 percent, and the simulated throughput of data flows in the presence of interfering transmitters with an error that is below 10 percent.     

基于背景差分和混合帧差的运动目标检测

针对利用核密度估计建立背景模型时计算量大,运动目标和外界环境容易发生变化,提出一种基于改进的核密度估计背景差分法和改进的混合帧差法相结合的运动目标检测方法。该方法在背景建模时,先对背景差分后的图像进行分块和分类,并简化了核密度估计的核函数,对前景块中的像素进行核密度估计,减少了计算量。在混合帧差法中增加了动态阈值,提高了对光线变化的适应性。实验结果表明该方法能够完整地提取出运动目标,提高了目标检测的准确率。