Unsupervised constrained radar imaging of low resolution targets

Abstract

A linear spectral estimation technique, the PDFT algorithm, is used as part of a nonlinear iterative reconstruction scheme to obtain improved radar images. The iterative PDFT algorithm is used to address the limited resolution problem inherent to imaging objects buried in soil and hidden under foliage. This is achieved by subsequent application of two properties of the PDFT algorithm: the energy parameter of the PDFT algorithm is used to determine the target shape, while the shape information in turn is used to obtain super-resolved images. We describe algorithms able to exploit both properties automatically and without manual intervention. Two methods are investigated in particular, one iteratively optimizing the constraints by monitoring the energy parameter, the other method computing energy values for all points, from which a weighted prior function is determined. In addition, we discuss variants of both algorithm which provide an optimized trade-off between computation time and performance. Additional attention is given to situations, where a known target is embedded in an unknown background. Imaging results are presented for both synthetic and measured data.     

Algorithms for data evaluation applied to the detection of buried objects

A non-iterative spectral estimation technique, the PDFT algorithm, is used to image buried objects from scattered field data. We discuss the PDFT as a generalized linear back-propagation method for Fourier transform data. Apart from its ability to incorporate prior knowledge about the target into the imaging model, it allows one to determine whether this prior information is consistent with the data. We discuss how this can be used to evaluate the quality of data sets. The PDFT is applied to real data of buried plastic land-mines and we show preliminary results indicating the potential of ground-penetrating radar for demining.     

基于随机点扩散函数的多帧湍流退化图像自适应复原方法

针对湍流退化图像随机性的问题,提出了一种基于随机点扩散函数的多帧湍流退化图像自适应复原方法。首先介绍了随机点扩散函数的图像退化模型,并分析了点扩散函数随机性对图像复原造成的影响,建立了基于随机点扩散函数的多帧图像退化模型。在此基础上,建立了基于多帧退化图像的全变分复原模型,利用前向后向算子分裂法对模型进行求解,提高了算法的运算效率。然后,提出了一种新的自适应正则化参数选取方法,该方法利用全变分复原模型的目标函数计算正则化参数,当正则化参数收敛时,复原图像的峰值信噪比达到最大值,因此利用目标函数的相对差值作为自适应算法迭代终止的条件,可以获得最佳复原效果。最后通过实验分析,算法中退化图像的帧数应不大于10帧。实验结果表明:当取10帧退化图像时,AFBS算法运算时间与单帧的FBS算法相当,信噪比增益为1.4 dB。本文算法对图像噪声有明显的抑制作用,对湍流退化图像可以获得较好的复原效果。     

Partition density functional theory and its extension to the spin-polarized case

Partition density functional theory (PDFT) [P. Elliott, K. Burke, M.H. Cohen, and A. Wasserman, Phys. Rev. A 82 (2), 024501 (2010)] is a formally exact method for obtaining molecular properties from Kohn–Sham calculations on isolated fragments. Here, we express the partition energy of PDFT as an implicit functional of the molecular spin-densities for a given choice of fragmentation, and use the principle of von Barth and Hedin to formulate the spin-decomposed version of PDFT. We introduce a partition energy functional of the spin-up and spin-down electronic densities and derive the associated polarized partition potentials, which are found to be global quantities that influence every fragment in the molecule. Along with the formal theory, we propose a simplified approach to computing the spin-partition potentials, and illustrate its utility and accuracy with two simple examples. Finally, we propose a viable approach to including external electric and magnetic fields in the framework of spin-PDFT.     

保留边界特征的深度图像增强算法研究

针对现有深度图像增强算法存在边界保留特性差的问题,提出梯度掩模导向联合滤波(gradient mask guided joint filter, GMGJF)算法。利用深度图像进行Sobel梯度变换获取边界方向信息,利用深度图像空洞区域生成空洞掩模,再以边界方向和空洞掩模为导向联合彩色图像对深度图像进行迭代高斯滤波和空洞填充。实验结果表明,GMGJF算法的PSNR(peak signal to noise ratio)、SSIM(structural similarity index measure)比IMF(iterative median filter)、GF(guided filter)、JBF(joint bilateral filter)算法的PSNR、SSIM至少提高了3.50%和1.07%,不仅去噪能力、空洞填充能力最强,而且边界特征保持最好,有利于深度图像的特征提取与目标识别。     

分片光滑物态方程的能量方程非线性迭代解法

实际应用中的物态方程由分片光滑曲面拼接而成,拼接处存在间断.隐式求解相应的能量方程时,经常出现迭代收敛慢的情况和非物理解.本文通过构造对应的新的非线性问题,提出一种非线性迭代算法.该算法适用于求解有间断的分片光滑物态方程的非线性能量方程,其中引入一个度量能量变化的参数用于自动判断跳段是否发生,在求解时无需事先知道物态方程间断的位置,且能精确计算物态方程间断带来的能量盈亏,用于评估物态方程间断对能量的影响.典型算例验证了新算法具有稳定的收敛性,并给出符合物理规律的解.     

Iterative reconstruction algorithm for optoacoustic imaging

Optoacoustic imaging is based on the generation of thermoelastic stress waves by heating an object in an optically heterogeneous medium with a short laser pulse. The stress waves contain information about the distribution of structures with preferential optical absorption. Detection of the waves with an array of broadband ultrasound detectors at the surface of the medium and applying a backprojection algorithm is used to create a map of absorbed energy inside the medium. With conventional reconstruction methods a large number of detector elements and filtering of the signals are necessary to reduce backprojection artifacts. As an alternative this study proposes an iterative procedure. The algorithm is designed to minimize the error between measured signals and signals calculated from the reconstructed image. In experiments using broadband optical ultrasound detectors and in simulations the algorithm was used to obtain three-dimensional images of multiple optoacoustic sources. With signals from a planar array of 3x3 detector elements a significant improvement was observed after about 10 iterations compared to the simple radial backprojection. Compared to conventional methods using filtered backprojection, the iterative method is computationally more intensive but requires less time and instrumentation for signal acquisition.     

基于形状特征的水声图像小目标识别方法

为了抑制背景噪声,提高目标识别准确率,该文提出一种基于形状特征的水声图像小目标识别方法。对含有目标的水声图像进行非局部均值去噪处理后,使用OTSU算法自适应选取阈值对去噪图像进行二值化分割,结合形态学处理获得分割后的目标区域;提取目标区域的矩形度、圆形度、几何不变矩等各项形状参数,将目标的特征向量输入随机森林分类器实现对目标形状的识别。在仿真和实测数据集上分别进行了实验,结果表明,该方法对水声图像中的目标具有较高的识别率,可以实现不同高斯噪声背景下的目标识别,相较于其他方法在识别率上有一定提高。     

Computerized ultrasonic tomography for testing solid propellant rocket motors

Certain types of defects, such as inhomogeneities in, for example, a plastic-like propellant, are not easily detected by pulse-echo techniques, so a through transmission technique is required. However, the shape of the test object may not permit transmission through the object in any required direction as is normally necessary for computerized ultrasonic tomography.A solid propellant rocket motor is such an object and in the course of this work a scanning technique is employed together with a suitable reconstruction algorithm to obtain a reconstructed image of the cross-section under investigation, overcoming the problem of not being able to transmit pulses through the object along every line normally required. Both a computer simulation and a real system were realized for the test object and images were produced from both. The time of flight of an ultrasonic beam through the specimen is the parameter used in the reconstruction (sound velocity measurement).     

基于深度玻尔兹曼模型的红外与可见光图像融合

为了克服红外与可见光图像融合时噪声干扰及易产生伪影导致目标轮廓不鲜明、对比度低的缺点,提出一种基于深度模型分割的图像融合方法.首先,采用深度玻尔兹曼机学习红外与可见光的目标和背景轮廓先验,构建轮廓的深度分割模型,通过Split Bregman迭代算法获取最优能量分割后的红外与可见光图像轮廓;然后再使用非下采样轮廓波变换对源图像进行分解,并针对所分割的背景轮廓采用结构相似度的规则进行系数组合;最后进行非下采样轮廓波反变换重构出融合图像.数值试验证明,该算法可以有效获取目标和背景轮廓均清晰的融合图像,融合结果不但具有较高的对比度,还能抑制噪声影响,具有有效性.     

Blur identification and restoration of degraded images using generalized cross-validation criterion

In this paper, we describe blur identification and restoration of noisy degraded images. The point-spread function (PSF) can be characterized by the quantity of blur. Thus the blur identification problem can be solved as a parameter estimation problem. The estimation method is a generalized cross-validation (GCV) criterion that is known as a powerful measure that can be used to choose the optimal regularization parameter without a priori knowledge about noise. We use the iterative damped-1east squares (DLS) algorithm which is based on the principle of damped least-squares for restoring noisy degraded images.     

非相干照明条件下的ptychographic iterative engine成像技术

在传统多波长相干衍射成像理论的基础上提出适用于 X-射线和电子束等非相干光源照明成像的改进多波长ptychographic iterative engine 方法, 同时将小孔形状和照明光谱信息用于叠代计算, 可以在非相干照明条件下精确重建出物体的强度透射像和相位透射像, 并对光源带宽对重建精度的影响进行了分析, 对于解决如何在非相干照明条件下对大尺寸物体进行精确相位成像的问题具有较好的科研和实用价值.     

Iterative Intensity Integration Technique (IIIT) for contouring reflective surfaces

Intensity Integration Technique (IIT) is an image correlation technique founded on energy conservation principle to contour reflective surfaces. The sum (integral) of intensities along pixel lines is identified as correlation parameter between the loaded and the unloaded images. At present, this procedure is employed to contour 2D reflective plates aided by projected gridlines onto reflected intensity images. Here, the gridline projection is dispensed with thereby simplifying the experimental procedure, with an iterative algorithm, Iterative Intensity Integration Technique (IIIT), developed to contour deformed reflective plates. In illustration, centrally as well as eccentrically loaded circular plates are studied. As a viable extension of IIIT, a method is suggested for generating digital Moiré fringes with pixel lines as grating lines.     

A circle similarity algorithm for an automatic circular decomposition of blood cell images

This paper presents an iterative algorithm for circular decomposition which investigates the separation of overlapped circular particles of a binary image, in order to locate their center coordinates and to estimate their radii. Since this algorithm is based on the measure of a circle similarity of an object in an image to execute a search for concavities, object segmentation and circle recognition, its implementation is simpler than the algorithm based on polygonal approximation. In this work we compare the accuracy and robustness of the proposed circle similarity algorithm with a polygonal approximation based algorithm using synthetic images and real blood cell images. Both the algorithms are able to decompose connected blood cells. However, the input parameters of the polygonal approximation method shows high sensitivity to the shape or agglomeration of an object, while the proposed algorithm demonstrates more stable performance.     

等离子体源离子注入过程中半圆形碗状样品的两维温度分布

等离子体源离子注入过程(PSII)中样品温度是一个非常重要的参量。由于注入到样品上的能量很大，导致样品温度很高，所以在实验中获知样品的温度分布有着很重要的意义。本文利用热传导方程建立了半圆形碗状样品内部温度升高模型，研究样品内温度演化过程。以注入离子束流作为能量输入项，热辐射为能量损失项，并考虑了热辐射过程中样品的形状因子的影响。考察了离子注入过程中样品上所施加负偏压的脉冲宽度和频率对样品温度分布的影响。研究结果显示，脉冲频率达到一定值后，样品温度不再随频率增加而升高。     

A FEM-based method to determine the complex material properties of piezoelectric disks

Numerical simulations allow modeling piezoelectric devices and ultrasonic transducers. However, the accuracy in the results is limited by the precise knowledge of the elastic, dielectric and piezoelectric properties of the piezoelectric material. To introduce the energy losses, these properties can be represented by complex numbers, where the real part of the model essentially determines the resonance frequencies and the imaginary part determines the amplitude of each resonant mode. In this work, a method based on the Finite Element Method (FEM) is modified to obtain the imaginary material properties of piezoelectric disks. The material properties are determined from the electrical impedance curve of the disk, which is measured by an impedance analyzer. The method consists in obtaining the material properties that minimize the error between experimental and numerical impedance curves over a wide range of frequencies. The proposed methodology starts with a sensitivity analysis of each parameter, determining the influence of each parameter over a set of resonant modes. Sensitivity results are used to implement a preliminary algorithm approaching the solution in order to avoid the search to be trapped into a local minimum. The method is applied to determine the material properties of a Pz27 disk sample from Ferroperm. The obtained properties are used to calculate the electrical impedance curve of the disk with a Finite Element algorithm, which is compared with the experimental electrical impedance curve. Additionally, the results were validated by comparing the numerical displacement profile with the displacements measured by a laser Doppler vibrometer. The comparison between the numerical and experimental results shows excellent agreement for both electrical impedance curve and for the displacement profile over the disk surface. The agreement between numerical and experimental displacement profiles shows that, although only the electrical impedance curve is considered in the adjustment procedure, the obtained material properties allow simulating the displacement amplitude accurately.     

Fixed-point quantum search

The quantum search algorithm consists of an iterative sequence of selective inversions and diffusion type operations, as a result of which it is able to find a state with desired properties (target state) in an unsorted database of size N in only sqrt[N] queries. This is achieved by designing the iterative transformations in a way that each iteration results in a small rotation of the state vector in a two-dimensional Hilbert space that includes the target state; if we choose the right number of iterative steps, we will stop just at the target state. This Letter shows that by replacing the selective inversions by selective phase shifts of pi/3, the algorithm preferentially converges to the target state irrespective of the step size or number of iterations. This feature leads to robust search algorithms and also to new schemes for quantum control and error correction.     

Real-time visual enhancement for infrared small dim targets in video

Visual enhancement for infrared small dim targets is a standing problem in infrared image processing. Existing approaches cannot enhance the target well and suppress the background simultaneously, especially for targets which are so faint that they are hardly visible. This paper proposes a novel real-time visual enhancement algorithm for infrared small dim targets in video by introducing temporal cues. In this work, Dynamic Programming Algorithm (DPA) is used to detect the target’s trajectory in the video and the target is enhanced through energy accumulation along the trajectory. The shape prior of the small dim target is adopted for background suppression and adaptive merging. Experimental results on real infrared small dim target videos indicate that the proposed algorithm can improve the visual quality of these types of images notably, especially for cases in which the target is hardly visible. In addition, the proposed algorithm takes on average 8.35 ms to process a 320 1 256 image, and thus meets the needs of real-time applications.     

A nonrigid registration algorithm for longitudinal breast MR images and the analysis of breast tumor response

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can estimate parameters relating to blood flow and tissue volume fractions and therefore may be used to characterize the response of breast tumors to treatment. To assess treatment response, values of these DCE-MRI parameters are observed at different time points during the course of treatment. We propose a method whereby DCE-MRI data sets obtained in separate imaging sessions can be co-registered to a common image space, thereby retaining spatial information so that serial DCE-MRI parameter maps can be compared on a voxel-by-voxel basis. In performing inter-session breast registration, one must account for patient repositioning and breast deformation, as well as changes in tumor shape and volume relative to other imaging sessions. One challenge is to optimally register the normal tissues while simultaneously preventing tumor distortion. We accomplish this by extending the adaptive bases algorithm through adding a tumor-volume preserving constraint in the cost function. We also propose a novel method to generate the simulated breast magnetic resonance (MR) images, which can be used to evaluate the proposed registration algorithm quantitatively. The proposed nonrigid registration algorithm is applied to both simulated and real longitudinal 3D high resolution MR images and the obtained transformations are then applied to lower resolution physiological parameter maps obtained via DCE-MRI. The registration results demonstrate the proposed algorithm can successfully register breast MR images acquired at different time points and allow for analysis of the registered parameter maps.     

红外目标湍流退化图像的优化复原算法

提出了基于最速下降法的湍流退化图像盲目复原算法。将图像转换到频域中，建立一个基于目标图像和点扩展函数频谱的目标函数，通过迭代方式采用最速下降优化方法来极小化该目标函数，并利用傅里叶变换和反变换将目标图像和点扩展函数在频域和空域之间进行变换，在每次迭代中交替加入约束条件进行反复修正，以便取得预期的图像恢复效果，增强算法的稳定性和抗噪能力。针对红外目标湍流退化图像，在微机上对算法进行了一系列复原验证实验。实验结果表明：该文算法复原效果稳定，抗噪能力强，具有实用价值。