Imaging resolution analysis in limited-view Laser Radar reflective tomography

In many applications of Laser radar reflective tomography, anisotropic resolution of images reconstructed from an incomplete set of reflective projections will degrade imaging quality. In this paper, we present the theoretical point spread function (PSF) of imaging system over full views for reflective tomography. The corresponding imaging resolution of the PSF was determined by Rayleigh's criterion, here the most common algorithm of filtered backprojection was used for image reconstruction. The theoretical imaging resolution was derived approximately from the range resolution resolved by the laser pulse. The simulated horizontal imaging resolutions of an ideal diffused single point target in different limited-views were compared with the theoretical value. Experimental reconstructed images from limit-view projections of letter “E” illustrated the effects of anisotropic resolution.     

Application of phase retrieval algorithm in reflective tomography laser radar imaging

We apply phase retrieval method to align projection data for tomographic reconstruction in reflective tomography laser radar imaging.In our experiment,the target is placed on a spin table with an unknown,but fixed,axis.The oscillatory motion of the target in the incident direction of the laser pulse is added at each view to simulate the real satellites random motion.The experimental simulation results demonstrate the effectiveness of this method to improve image reconstruction quality.Future research also includes the development of projection registration based on phase retrieval for targets with more complicated structure.     

傅里叶望远镜重构图像虚像分析

研究了采用T型激光发射阵列情况下傅里叶望远镜重构图像的虚像问题, 基于系统成像基本原理, 明确了虚像的来源. 分析认为, 发射光束在x和y轴扫描时, 在俯仰角误差的作用下, 抽取目标的空间频率和设定值之间存在一定的偏差; 当进行轴向和象限相位闭合、计算目标的单一傅里叶分量时, 该偏差会对频谱的频移造成随机的相位影响, 反映在空域上使得重构图像存在虚影现象. 在不同扫描方式情况下, 采用下一步外场实验参数, 通过计算机模拟证实了上述分析的正确性.     

Correlation recognition for range image of laser radar

The target recognition of laser radar becomes hot research in recent years, because laser radar can produce high space resolution and collect rich target information, such as range image, intensity image and Doppler image. In the vertical detection of laser radar, the problem of in-plane target rotation invariance is firstly solved. In the paper, a new support vector machine (SVM) correlation filter is presented, which simultaneously has the attractive attributes of SVM and common correlation filter. Exploiting the idea of margin of separation maximization, the design criterion is produced. The filter is synthetic by the multiple training images which are generated by rotating one image. The real range images of laser radar are used to finish the correlation experiments. The results show that the filter is not sensitive to the noise, the correlation peak is changed slightly for the different testing images, and the precision of location is high.This design way can be used in other recognition fields.     

四光束剪切相干成像目标重构算法研究

针对传统剪切光束成像技术的准实时性问题,提出用口字形排布的四束光代替传统L形三束剪切光照射目标,研究了四光束剪切相干成像目标重构算法.只需单次测量就能同时重构出四幅目标图像,减少了用于降低散斑噪声、获取高质量图像所需的测量次数,同时大大减少了多组发射时的光束切换次数,提高了成像效率.在算法实现中,通过最小二乘法恢复出四组波前相位,利用散斑幅值的简单代数运算恢复波前幅值,从而重构出目标图像.仿真结果表明,与传统方法相比,在图像质量相同的前提下,本文方法所需的数据采集时间减少了至少1/2,不但提高了目标重构效率,还可为远程运动目标的成像识别提供更好的手段.     

聚束非相干合成孔径激光成像雷达研究

反射层析激光成像雷达只能获得目标的二维轮廓像,不能对平面目标进行成像。报道了聚束模式下的非相干合成孔径激光成像雷达实验,在这种成像模式下,可以对二维平面目标进行图像重构。采用侧视观察的模式获取目标的角度-距离-强度信息,然后通过滤波反投影实现平面目标的图像重建,并进行了计算机仿真,证明了实验结果的正确性。该系统作为非相干合成孔径激光雷达的一种,实现了区别于目标轮廓的二维成像,具有一定的实际意义和使用价值。     

强激光远场光束质量参数的测试

 提出漫射红外成像-多点标校测量方法,用于测量强激光远场光束质量参数。在激光远场距离处设置漫反射靶板,用成像探测器摄取经靶面漫射的脉冲强激光光斑图像;在靶面中心处挖小孔,孔后放置能量探测器实时测量激光脉宽和峰值功率。同时对整个激光光斑图像进行能量定标,进而得出远场脉冲强激光的实际空间能量/功率分布、总能量,以及相应的光束质量参数。应用该测量方法,对高能TEA CO₂激光进行测量研究,测得其远场光束截面半径为80.2 mm,发散角为1.55 mrad。     

基于角度-多普勒分辨的反射层析激光成像雷达研究

设计了一种基于角度-多普勒分辨的接发同轴反射层析激光成像雷达系统,给出了基本成像原理和数学表达,相应分析了目标横向距离分辨率和单个角度采样时间的关系。并在实验室平台上模拟远场衍射传输,获取探测目标的角度-多普勒分辨的反射投影图,采用滤波反投影算法实现目标横截面图像重建。此方法采用相干外差探测,可以大大提高雷达接收信号灵敏度,同时不涉及光频空间相位和时间相位,成像中没有相位匹配过程,降低了实施技术难度,具有一定的实际意义和使用价值。     

主被动光学图像融合技术研究

本文应用扫描式激光成像雷达获取试验数据并实现对激光数据的三维成像处理,给出了基于目标特征的激光雷达图像与被动光学图像的数据融合方法,实现了激光图像和光学图像间的三维融合。试验结果表明,本文所提出的基于目标特征的两种不同质图像间的融合方法是可行的,融合后的图像具有丰富的光谱信息和三维立体信息。     

Infra-red heterodyne laser radar for remote sensing of air pollutants by range-resolved differential absorption

An infra-red heterodyne laser radar scheme incorporating range-resolved differential absorption using elastically backscattered, pulsed signal from distributed particles in the atmosphere is proposed and analysed. The basic requirements of the system arrangement and operating parameters involved in this scheme are discussed in detail. This method is shown to offer a remote and spatially-resolved measurement of various molecuar pollutants dispersed in the air for ranges up to several km and detection sensitivities to less than 0.1 ppm with laser pulses of 100 W average power. This power is 10³ to 10⁶ times smaller than that required with the conventional direct detection technique in the infra-red. The measuring accuracy and its limiting processes inherent to the infra-red range-resolved differential absorption method are also analysed.     

4-D image reconstruction for Streak Tube Imaging Lidar

The Streak Tube Imaging Lidar (STIL) which is the flash laser radar is developed in recently years. It can output the 4-D image (3-D range image + 1-D intensity image). The core part of STIL is the streak tube, which is a line array detector. STIL can directly collect the image of returned light pulse, and consequently, it can’t output the 4-D target image. In the paper, the peak detection as the reconstruction algorithm is used to reconstruct the multiple streak tube images, and the clear 4-D target images are obtained. The outdoor imaging experiments are completed for the far distance buildings. The reconstruction for the multiple streak tube images is finished, and the results state that the peak detection algorithm can output the high-resolution 4-D target images. Original Text ? Astro, Ltd., 2009. The article is published in the original.     

Fast Estimation of Scatter Components Using the Ordered Subset Expectation Maximization Algorithm for Scatter Compensation

In this work we propose a method for scatter compensation in single photon emission computed tomography imaging, by which we can estimate the scatter components in projections in high speed with good accuracy. The method is that we first estimate the scatter components in projections based on scatter response kernels by one time of ordered subsets expectation maximization iterative reconstruction, and then subtract the estimated scatter components from the projections and complete reconstruction by filtered back-projection method. The principle is that the image corresponding to the scatter components in projections consists largely of low-frequency components of an activity distribution; these low-frequency components will converge faster than the high ones in iterative reconstruction. Therefore, we can estimate the low-frequency component image before the image converges with the high-frequency ones, and obtain the scatter components by re-projecting the low-frequency component image with scatter response kernels. The effects of the proposed method were compared with the dual- and triple-energy window methods using experimental measurements. The results show that good accuracy in estimated scatter components, good uniformity of scatter compensation at the center and the side of an object, and good noise property can be acquired by this method.     

Burst imaging: rotation artifacts and how to correct them

The effect of coherent rotational motion on images acquired with the ultrafast single-shot spin-echo Burst sequence has been analyzed. Previous experience has demonstrated that sample rotation during Burst experiments has the potential to cause severe image artifacts. In this paper we show that no distortions are visible when the readout gradient is parallel to the rotation axis, but that there is a very distinctive behavior for the case of the rotation axis orthogonal to the imaging plane. The mathematical expression that describes the resulting signal is presented and is used as a basis for a method of correcting the k-space data. The conditions under which undistorted images may be recovered are discussed. It is shown that there is an asymmetry, dependent on the rotation direction, in both the manifestation of the artifact and the range of angular velocities over which one can correct the images. Data from an agar gel phantom rotating at a known rate are used to show how the theory is successful at reconstructing images, with no free parameters. The range of angular velocities over which correction is possible depends on the timing parameters of the pulse sequence, but for these data was -0.016 < omega less, similar 0.1 revolutions/s. Volunteer experiments have confirmed that the theory is applicable to patient motion and can correct motional distortion even when the exact rate is not known a priori. By optimizing the reconstruction to restore a known sample geometry/aspect ratio, an estimate of the rotation angular frequency is obtained with a precision of +/-10%.     

Unsupervised constrained radar imaging of low resolution targets

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.     

Assessment and robust reconstruction of laser radar signals

In direct-detection imaging, laser radar speckle noise, drop-outs, and outliers have to be considered in order to ensure high accuracy and reliability of measurement data. The most common approach for the stabilization of laser radar data is temporal averaging over several shots. This, however, is not in all cases the best method for the reconstruction of noisy image data. It is shown that principal component reconstruction can yield a remarkable improvement of accuracy and robustness of range data.     

基于快速轮廓转动力矩特征的激光主动成像目标识别

针对激光主动成像的图像特性,提出一种基于快速轮廓转动力矩的目标识别方法。将转动力矩的概念引入目标识别中,提出的快速轮廓转动力矩特征(FCTF)不仅包含了轮廓的尺寸、位置、规则度以及目标的亮暗等信息,同时对于旋转、尺度缩放等变换具有不变性。采用转动力矩的快速计算方法,提高了识别算法的计算效率。识别算法首先使用最大稳定极值区域(MSER)算法检测出目标特征区域,并将其变换为圆形区域,然后结合快速转动力矩特征算法提取出目标区域的局部不变特征,最后输入训练好的支持向量机分类器进行识别。实验结果表明相比于已有的激光主动成像目标识别方法,所提算法对于旋转、仿射变换均具有更高的识别率,同时单帧平均运算时间为9.68 ms,满足激光主动成像目标识别系统实时性的要求。     

Determination of exact rotation angle and discrimination for rotated images

The complex frequency scaling property of Fourier transforms may be very effective for the determination of exact image rotation angle in application areas such as defense, manufacturing agriculture and commerce. In this paper, we exploit the complex frequency scaling property of Fourier transform to determine the exact angle of rotation of a target image with respect to reference image. We also investigate the validity of the developed algorithm using occluded target images. Further, we extend our algorithm to differentiate between different but similar rotated target images. We use both gray scale and DARPA's moving and stationary target recognition program's synthetic aperture radar images to validate our algorithm.     

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.     

Enhanced resolution for EPR imaging by two-step deblurring

The broad spectrum of spin probes used for electron paramagnetic resonance imaging (EPRI) result in poor spatial resolution of the reconstructed images. Conventional deconvolution procedures can enhance the resolution to some extent but obtaining high resolution EPR images is still a challenge. In this work, we have implemented and analyzed the performance of a postacquisition deblurring technique to enhance the spatial resolution of the EPR images. The technique consists of two steps; noniterative deconvolution followed by iterative deconvolution of the acquired projections which are then projected back using filtered backprojection (FBP) to reconstruct a high resolution image. Further, we have proposed an analogous technique for iterative reconstruction algorithms such as multiplicative simultaneous iterative reconstruction technique (MSIRT) which can be a method of choice for many applications. The performance of the suggested deblurring approach is evaluated using computer simulations and EPRI experiments. Results suggest that the proposed procedure is superior to the standard FBP and standard iterative reconstruction algorithms in terms of mean-square-error (MSE), spatial resolution, and visual judgment. Although the procedure is described for 2D imaging, it can be readily extended to 3D imaging.