An infrared small target detection algorithm based on high-speed local contrast method

Small-target detection in infrared imagery with a complex background is always an important task in remote sensing fields. It is important to improve the detection capabilities such as detection rate, false alarm rate, and speed. However, current algorithms usually improve one or two of the detection capabilities while sacrificing the other. In this letter, an Infrared (IR) small target detection algorithm with two layers inspired by Human Visual System (HVS) is proposed to balance those detection capabilities. The first layer uses high speed simplified local contrast method to select significant information. And the second layer uses machine learning classifier to separate targets from background clutters. Experimental results show the proposed algorithm pursue good performance in detection rate, false alarm rate and speed simultaneously.     

Scale-space point spread function based framework to boost infrared target detection algorithms

Small target detection is one of the major concern in the development of infrared surveillance systems. Detection algorithms based on Gaussian target modeling have attracted most attention from researchers in this field. However, the lack of accurate target modeling limits the performance of this type of infrared small target detection algorithms. In this paper, signal to clutter ratio (SCR) improvement mechanism based on the matched filter is described in detail and effect of Point Spread Function (PSF) on the intensity and spatial distribution of the target pixels is clarified comprehensively. In the following, a new parametric model for small infrared targets is developed based on the PSF of imaging system which can be considered as a matched filter. Based on this model, a new framework to boost model-based infrared target detection algorithms is presented. In order to show the performance of this new framework, the proposed model is adopted in Laplacian scale-space algorithms which is a well-known algorithm in the small infrared target detection field. Simulation results show that the proposed framework has better detection performance in comparison with the Gaussian one and improves the overall performance of IRST system. By analyzing the performance of the proposed algorithm based on this new framework in a quantitative manner, this new framework shows at least 20% improvement in the output SCR values in comparison with Laplacian of Gaussian (LoG) algorithm.     

基于瑞利熵的多无源传感器数据关联算法

针对当前多无源传感器数据关联算法构造关联代价时,未考虑位置估计不确定性所引入的误差,提出一种基于位置估计不确定性的被动传感器数据关联算法。首先通过量测与伪量测概率密度函数之间的瑞利熵构建关联代价函数,以准确描述两个相似的概率密度函数之间差异,然后通过具体实验测试本文算法的有效性和优越性。实验结果表明,相对于当前经典的数据关联算法,本文算法提高了数据关联的正确率和速度,具有更高的实际应用价值。     

基于小波高频距离像的红外小目标检测

针对远距离复杂背景下红外小目标检测问题,本文提出了一种基于小波高频距离像的方法。该方法首先将处理空间变换到小波域,通过分析残留背景、目标和噪声系数在高频子带的差异,定义基于邻域均值的子带系数表达形式,构造高频子带系数的中心向量,对小波高频图像进行综合形成距离像,得到红外复杂背景的抑制结果。在此基础上,利用恒虚警率算法将单帧背景抑制图像分割成候选目标、残留背景和噪声像素点。最后,在时间域基于目标运动的相关性,利用管道滤波实现红外小目标的最终检测。仿真实验结果表明,相对于经典算法,本文方法可以实现对红外复杂背景的有效抑制,增强目标信号的强度,准确稳定的从红外复杂背景中检测出小目标。     

基于ZigBee网络和超声定位的智能跟随小车

基于成熟的IEEE802.15.4协议和ZigBee无线模块,结合超声定位,设计了一种新颖的智能跟随系统。设计的核心为PIC18F4620单片机和MRF24J40MA无线收发模块,通过无线收发来完成节点间的识别与同步,同时以超声测距系统完成对被跟踪目标的定位,通过控制驱动电机动作实现对指定目标的定距离跟随。控制网络以子网的形式控制不同系统的分时定位跟随,同时管理各移动定位系统的入网和切换。样机测试结果表明系统达到了预期的跟随设计要求,具有一定的工程使用价值。     

一种改进的三帧差分运动目标实时检测算法

针对传统的三帧差分法提取的运动目标存在大量的噪声和空洞,提出了一种改进的三帧差分运动目标实时检测算法。该算法采用Surendra背景提取算法提取有效背景,对视频流中连续的三帧图像分别进行背景减除,得到的结果作为反馈对背景进行选择性更新,利用HSV颜色空间去除阴影后进行三帧差分,将差分结果进行“与”运行,通过将中间帧背景减除结果与“与”运算的结果进行“或”运算,这样可以得到运动目标的完整信息。实验结果表明,该算法能够快速、完整、准确地检测出运动目标,可有效应用于实时监控系统。     

黑腔冷冻靶传热与自然对流的数值模拟研究

惯性约束聚变的设计要求在靶丸内形成均匀光滑的氘氚冰层, 靶丸周围的热环境对冰层的质量特别是低阶粗糙度有很大的影响. 本文对自主研发的黑腔冷冻靶实验装置中的热物理问题展开了数值模拟, 重点考察了黑腔冷冻靶的传热和流体力学特性. 通过参数分析得到了自然对流对靶丸温度均匀性产生影响的临界条件. 比较了黑腔不同布置朝向时的流场和温度分布, 结果显示黑腔水平布置时自然对流更加强烈, 造成的靶丸温度不均匀性也更大. 在此基础上, 讨论了消除自然对流影响的可能性, 结果发现仅当黑腔垂直布置时利用黑腔分区方法能够消除对流效应对靶丸温度不均匀性的影响而黑腔水平布置时不能消除. 研究结论对于实验中冷冻靶结构的设计、改进和实验的开展等具有指导意义.     

三维斑点追踪成像评价甲状腺功能亢进患者左心室收缩功能改变的应用价值

目的 探讨三维斑点追踪成像（3D-STI）技术在评价甲状腺功能亢进(甲亢)患者左心室整体收缩功能中的应用价 值。方法 选择50 例甲状腺功能亢进患者与45 例健康志愿者,获取心尖四腔心切面动态图像,存储左心室三维全容积动态图像后,运用3D-STI 软件进行脱机分析,得到两组收缩期左心室整体纵向峰值应变（GLS）、圆周峰值应变（GCS）、左心室扭转度角度峰值(LV-tw)、左心室扭力（LV-tor）、左心室心底水平旋转角度峰值（Prot-B）、左心室心尖水平旋转角度峰值（Prot-A）及左心室射血分数（LVEF）等,比较两组三维应变（3DS）指标之间的差异。结果 与正常对照组比较,甲亢组的左心室收缩功能增强,GLS、GCS 分别为（-20.47±3.08）% vs.（-18.52±4.77）%、（-28.98±3.00）% vs.（-25.88±2.12）%,两组差异均有统计学意义（均P＜0.05）;甲亢组LV-tw、LV-tor、LVProt-A、LVProt-B 均较正常对照组略有增加,但差异均无统计学意义（均P＞0.05）。结论 3D-STI 可无 创、敏感检测甲亢患者左心室三维应变,为临床客观评估甲亢左心室收缩功能提供一种新方法。     

Computer-aided design and discovery of protein–protein interaction inhibitors as agents for anti-HIV therapy

Protein–protein interactions (PPI) are involved in most of the essential processes that occur in organisms. In recent years, PPI have become the object of increasing attention in drug discovery, particularly for anti-HIV drugs. Although the use of combinations of existing drugs, termed highly active antiretroviral therapy (HAART), has revolutionized the treatment of HIV/AIDS, problems with these agents, such as the rapid emergence of drug-resistant HIV-1 mutants and serious adverse effects, have highlighted the need for further discovery of new drugs and new targets. Numerous investigations have shown that PPI play a key role in the virus’s life cycle and that blocking or modulating them has a significant therapeutic potential. Here we summarize the recent progress in computer-aided design of PPI inhibitors, mainly focusing on the selection of the drug targets (HIV enzymes and virus entry machinery) and the utilization of peptides and small molecules to prevent a variety of protein–protein interactions (viral–viral or viral–host) that play a vital role in the progression of HIV infection.     

Cell Tracking with Caged Xenon: Using Cryptophanes as MRI Reporters upon Cellular Internalization

Caged xenon has great potential in overcoming sensitivity limitations for solution‐state NMR detection of dilute molecules. However, no application of such a system as a magnetic resonance imaging (MRI) contrast agent has yet been performed with live cells. We demonstrate MRI localization of cells labeled with caged xenon in a packed‐bed bioreactor working under perfusion with hyperpolarized‐xenon‐saturated medium. Xenon hosts enable NMR/MRI experiments with switchable contrast and selectivity for cell‐associated versus unbound cages. We present MR images with 10³‐fold sensitivity enhancement for cell‐internalized, dual‐mode (fluorescence/MRI) xenon hosts at low micromolar concentrations. Our results illustrate the capability of functionalized xenon to act as a highly sensitive cell tracer for MRI detection even without signal averaging. The method will bridge the challenging gap for translation to in vivo studies for the optimization of targeted biosensors and their multiplexing applications.