雷达模拟训练系统电视跟踪视景仿真实现

电视跟踪是雷达系统多模式跟踪方式中重要的一种,基于图像绘制技术实现了电视跟踪系统的视景仿真。详细描述了电视跟踪视景仿真的实现方法,包括系统设计、序列图像采集方法、全景图像的合成算法以及视景图像生成算法,并进行了算法优化和视景仿真实现。该方法已成功应用于某多功能相控阵雷达模拟训练系统的开发,仿真效果较为逼真。     

高动态条件下增量惯导信息辅助的空地红外弱小移动目标检测算法（特邀）

红外弱小移动目标检测技术是计算机视觉的研究热点和难点。针对机载高动态条件下的空地目标检测存在的场景变化动态、背景干扰强度大、目标运动规律未知等挑战,提出了一种新型的基于增量惯导信息辅助的空地红外弱小移动目标检测算法。为了解决传统惯导信息预测的漂移误差问题,提出了增量惯导信息概念,设计了增量惯导信息的位置预测模型,实现了对目标点的准确预测。构建了基于增量惯导信息辅助与背景差分的移动目标检测框架,通过增量惯导信息对不同位姿下的成像进行校正,引入基于爬山法互相关匹配算法计算校正后图像的平移参数,采用高斯加权对背景图像进行估计,最后通过图像分割检测弱小移动目标。仿真实验验证了文中设计检测算法的有效性和精确性。     

基于DSP的智能相关电视跟踪系统

介绍了一种基于TMS32OC6202的数字式智能相关电视跟踪系统的设计,该系统以DSP图像处理板为核心,采用双CPU的系统结构设计,使图像处理系统和云台控制系统分离,增强了系统的实时性、可靠性.并介绍了本系统采用的图像分割及跟踪算法.     

3D电视视差舒适度客观评价

视差是双目立体视觉的重要研究方向,也是影响人眼观看3D电视舒适度的重要因素,本文阐述了双目立体视觉和视差的概念、约束条件,介绍了3D电视视频图像质量评价的方法、发展以及相关标准,最后分析视差舒适度客观评价的相关算法,并通过实验对比各种算法的提取精度和效果,设计和实现3D电视视差舒适度客观评价软件。     

实时目标跟踪系统处理平台设计及快速算法研究

为解决电视捕获跟踪瞄准系统中系统的实时性与算法复杂性之间的矛盾,设计了以高性能的DSP芯片TMS320C6416为核心处理器,结合大规模可编程逻辑器件CPLD进行逻辑控制以及现场可编程门阵列FPGA对采集的视频数字图像做预处理的实时目标识别跟踪处理平台。同时改进了目标识别算法,提出一种基于遗传算法的快速图像相关匹配算法。重点介绍了该实时数字图像处理系统的硬件组成、工作原理和新的图像相关匹配算法。结果表明系统具有较高的实时性和稳定性。     

消除运动模糊的隔行/逐行转换算法

针对一般算法的缺点，即把输入的隔行扫描电视场图像转换成逐行扫描时会产生的运动模糊现象，提出了一种消除模糊的算法，从而大在提高电视墙的图像显示质量，并针对这一应用场合，提出了利用电视视频信号特点的运动估计算法。     

初始段安控图像目标识别方法研究

该研究为实现发射场初始段安控电视系统数字化图像采集、处理和存储展开讨论。采用形态学边缘检测算法、霍夫变换直线检测算法和光流法运动检测算法,利用火箭发射初始段安控电视录像进行测试实验,实现了对发射场初始段火箭箭体的识别。该研究使用数字化图像处理方法对现有的安控电视系统进行有效改进,为安控图像实时判读提供了可靠的依据,并为下一步研究提供了有意义的参考。通过对上述几种之间的特点和处理所需的时间的比较分析,形态学边缘检测算法的效果优于其他两种方法。     

一种运动自适应去隔行算法及硬件实现

去隔行算法是电视扫描格式转换和数字视频处理的一项关键技术.本文分析了现有的各种去隔行算法,在此基础上,采用了一种运动自适应去隔行算法.该算法通过运动检测将图像中的像素进行分类,针对不同类型的像素点自适应的采取不同的插值算法,提高了图像的质量.同时与基于块匹配的运动补偿去隔行算法相比,易于硬件实现.     

基于区域模板相关的图像匹配方法研究

传统的图像相关匹配方法是利用求取对应像素灰度的相关性进行图像之间的相似度量的。由于参考图和实测图之间存在着灰度差异、模糊、噪声以及局部遮挡等,这就使得仅依靠图像灰度相关进行匹配的算法性能受到影响。基于图像分割后的区域是比像素灰度更高一级的图像表述,利用势函数聚类自适应多阈值图像分割技术,提出了一种对图像的加权区域模板相关匹配的算法。这种算法建立了一种目标区域隶属度的相关度量方法。试验结果表明了该算法在多种图像变形情况下的有效性。     

导频辅助MC-CDMA系统的解相关干扰消除多用户检测器

我们提出了一种新的基于导频辅助的MC-CDMA系统的信道估计和解相关、解相关干扰消除检测器。这里的基于导频辅助的MC-CDMA系统的信道估计采用了一种新的算法．通过设计每个用户的导频信息．无需增加系统的过多负担,就可以实现较好的信道估计。解相关检测器采用了伪逆算法,解相关干扰消除检测器则用解相关检测器的输出作为一级输入,结合并行干扰消除算法。仿真结果显示了信道估计和多用户检测器的较好性能。     

激光干扰电视制导导弹建模与仿真

以激光对电视制导导弹的干扰研究为出发点,经过对图像模拟的需求分析,建立了目标透视投影模型,生成目标和背景的近似二值图像,进行了激光对电视制导导弹的饱和干扰仿真.用透视投影法生成近似目标和背景的二值图像方法简单,避免了逼真的图像模拟实现难度大的问题.仿真结果表明所建模型合理,初步得到了激光饱和干扰电视制导导弹的干扰效果.     

Correlation-coefficient-based fast template matching through partial elimination

Partial computation elimination techniques are often used for fast template matching. At a particular search location, computations are prematurely terminated as soon as it is found that this location cannot compete with an already known best match location. Due to the nonmonotonic growth pattern of the correlation-based similarity measures, partial computation elimination techniques have been traditionally considered inapplicable to speed up these measures. In this paper, we show that partial elimination techniques may be applied to a correlation coefficient by using a monotonic formulation, and we propose basic-mode and extended-mode partial correlation elimination algorithms for fast template matching. The basic-mode algorithm is more efficient on small template sizes, whereas the extended mode is faster on medium and larger templates. We also propose a strategy to decide which algorithm to use for a given data set. To achieve a high speedup, elimination algorithms require an initial guess of the peak correlation value. We propose two initialization schemes including a coarse-to-fine scheme for larger templates and a two-stage technique for small- and medium-sized templates. Our proposed algorithms are exact, i.e., having exhaustive equivalent accuracy, and are compared with the existing fast techniques using real image data sets on a wide variety of template sizes. While the actual speedups are data dependent, in most cases, our proposed algorithms have been found to be significantly faster than the other algorithms.     

基于Radon逆变换分解的超短扫描锥束重建

在3-D Radon逆变换的分解的基础上,推导出一种属于后偏导类型的锥束重建算法.与原类型算法相比,该算法由于引进了关于锥向变量偏导数的相关运算,而获得了与前偏导类型算法相近的重建结果.利用转角纠正因子对重建公式进行修正,从而进一步扩大了锥向重建范围.采用3-D Shapp-Logan头模型进行了计算机模拟,实验结果验证了算法的有效性.     

CO2胁迫下大豆叶片红边位置最优算法的研究

利用红边参数反演植被特征是定量遥感研究的热点问题之一,红边参数中的红边位置与植被参数显著相关,是监测植被胁迫的一个非常敏感的指标。采用最大一阶导数法、拉格朗日内插法、线性外推法、四点内插法、倒高斯模型法、多项式拟合法六种方法分别计算出不同浓度CO2泄漏胁迫下大豆叶片的红边位置,分析并比较不同算法提取的红边位置变化特征,以确定监测CO2泄漏胁迫下大豆叶片的最佳红边位置的算法。结果表明：提取的红边位置均与大豆叶片叶绿素含量呈极显著的线性相关。其中,最大一阶导数法和拉格朗日内插法相关程度最高,且最大一阶导数法计算简单、稳定性较好,因此可以利用最大一阶导数法提取的红边位置反映大豆叶片叶绿素含量变化,进而监测CO2地质储存泄漏问题。     

Development of an automated method for detecting mammographicmasses with a partial loss of region

Recently, we have been developing several automated algorithms for detecting masses on mammograms. For our algorithm, we devised an adaptive thresholding technique for detecting masses, but our system failed to detect masses with a partial loss of region that were located on the edge of the film. This is a common issue in all of the algorithms developed so far by other groups. In order to deal with this problem, we propose a new method in the present study. The partial loss masses are identified by their similarity to a sector-form model in the template matching process. To calculate the similarity, four features are applied: 1) average pixel value; 2) standard deviation of pixel values; 3) standard correlation coefficient defined by the sector-form model; and 4) concentration feature determined from the density gradient. After employing the new method to 335 digitized mammograms, the detection sensitivity for the partial loss masses jumped from 70% to 90% when the number of false positives was kept constant (0.2/image). Moreover, a combination of the existing method and the new method improved the true-positive rate up to 97%. Such results indicate that the new technique may improve the performance of our computer-aided diagnosis system for mammographic masses effectively.     

空地电视制导导弹作战使用研究

研究空地电视制导导弹的作战使用,包括电视跟踪方式和电视导引头作用距离的影响因素,有利于更好地制定使用该种武器的战术,充分发挥其作战效能。通过ADC法建立的空地导弹的作战效能评估模型表明,与高炮相比,地空导弹的拦截是导弹的主要威胁,选择合适的导弹巡航高度,可以明显改善导弹的安全性能,对于提高空地电视制导导弹的作战效能提供了一种新思路。     

Fast adaptive optimization of weighted vector median filters

Weighted vector median (WVM) filters are effective tools for multichannel signal processing. To obtain the desired filtering behavior and characteristic, the WVM filter weights must be determined in an appropriate manner. In this paper, we first analyze previously defined approaches for WVM filter optimization and show their drawbacks related to derivative computation and vector direction information utilization. Based on this analysis, we propose two fast adaptive algorithms for WVM filter design. Proposed Algorithm I computes locally optimal weight changes at each iteration and updates the filter weights accordingly. This algorithm does not involve derivative computation, thus eliminating the instability caused by derivative approximations utilized in previous approaches. Proposed Algorithm II extends the results from established marginal weighted median optimization methods to the vector case by error metric generalization. Both algorithms can be applied to WVM filters using the L/sub p/ norm, while Algorithm I can operate on more general distance metrics. The presented simulation results show that both algorithms are effective, fast, and stable; they perform well under a wide range of circumstances.     

人在回路电视制导导弹最优发射区的确定

导弹发射区的确定直接决定着武器作战使用效果。针对人在回路电视指令制导导弹,通过分析影响发射区的因素,对传统的图论算法进行改进使其适用于解决此类问题,编写了具有很强实用性和可扩展性的武器最优发射区计算软件,最后通过实例仿真验证了软件的正确性和普适性。     

基于matlab的电视制导空地导弹动态仿真

采用模块化设计方法建立了中程电视制导空地(面)导弹的仿真模型,并应用matlab实现了仿真工具箱,对导弹的制导过程进行了全弹道仿真,为电视制导导弹的分析与设计提供了有力的工具．     

A Two-Stage Fusing Method of Reconstruction Algorithms for Compressed Sensing

There are still many algorithms proposed recently to reconstruct signals in Compressed Sensing (CS) setup. However, how to reconstruct sparse signals accurately with fewer measurements and less time is still a problem. It is interesting to observe that algorithms with poor performance do not mean a complete failure, as their support set may include some correct indices that some algorithms with good performance may not find out. Because of this, people proposed some fusing method using modified algorithms and partial support set, however, the reliability of the set is the key to the algorithm, and the modified method of different algorithms and the reconstruction performances of different modified algorithms are still needed to be verified. In this paper, we propose a two-stage fusing method for Compressed Sensing algorithms. From existing algorithms, we choose one as the main algorithm, some other as prior algorithms and run them in different stages. In the first stage we get high-accuracy atomic set from the prior algorithms and in the second stage we use the atomic set as the partial support set and fuse it with the main algorithm adaptively to improve the sparse signal reconstruction. The proposed method is suitable for most CS algorithms which work with different principles. According to the simulation results, the proposed method improves the performance of participating algorithms and is superior to other fusing methods in both reconstruction accuracy and reconstruction time.