光子成像系统信号与噪声的统计特性分析

在去除光子图像的本底噪声时,根据微弱点目标的探测统计特性,以泊松分布均值与方差相等的特点为判据,提出了一种确定阈值选取范围的新方法。利用点过程的分析方法研究了光子受限点目标的探测统计特性,并进行了实验研究,结果表明光子受限点目标的探测统计特性服从平稳泊松点过程。利用以上分析方法可以快速地获得微弱点目标事件的期望发生率,以及在下一段时间内目标至少再出现一次的概率,从而为后续的目标探测、跟踪以及位置预测奠定了基础。     

光子成像静止点目标的管道滤波探测方法

构建了具有单光子成像能力的光子成像系统,提出应用管道滤波方法实现对光子受限静止点目标的探测。分析了光子图像静止点目标与点状噪声特征,根据静止点目标在序列图像中位置的确定性以及噪声点的不相关性,研究了基于管道滤波的光子成像静止点目标探测方法。为降低目标探测的虚警概率,优化了管道滤波直径。以实验采集得到的多组光子图像序列为样本,获得了探测概率、虚警概率与信号光子数、噪声光子数、管道长度以及检测阈值的关系。检测结果显示,对信号与噪声的平均发生率为0.4和5.215的序列图像,当管道长度为9、检测阈值为2时,探测概率达0.9以上且虚警概率〈0.08。对比多组图像序列的检测结果表明,影响探测概率的主要参数是信号光子数,而影响虚警概率的主要参数是噪声光子数。     

基于光电双开关的单光子同步探测

提出了一种基于光电双开关进行同步测量单光子的方法.这种测量方法能够有效抑制背景光以及由背景光引起的后脉冲和死时间对单光子测量的影响,有效地减少了单光子探测中的误计数,改善了单光子测量的信噪比.同时,避免了单光子探测器通常工作在门控电压方式下产生自发光子辐射的缺点.     

An Entropy-Based Anti-Noise Method for Reducing Ranging Error in Photon Counting Lidar

Photon counting lidar for long-range detection faces the problem of declining ranging performance caused by background noise. Current anti-noise methods are not robust enough in the case of weak signal and strong background noise, resulting in poor ranging error. In this work, based on the characteristics of the uncertainty of echo signal and noise in photon counting lidar, an entropy-based anti-noise method is proposed to reduce the ranging error under high background noise. Firstly, the photon counting entropy, which is considered as the feature to distinguish signal from noise, is defined to quantify the uncertainty of fluctuation among photon events responding to the Geiger mode avalanche photodiode. Then, the photon counting entropy is combined with a windowing operation to enhance the difference between signal and noise, so as to mitigate the effect of background noise and estimate the time of flight of the laser pulses. Simulation and experimental analysis show that the proposed method improves the anti-noise performance well, and experimental results demonstrate that the proposed method effectively mitigates the effect of background noise to reduce ranging error despite high background noise.     

基于背景特征参数的激光雷达目标检测

激光雷达的弱小目标检测是激光雷达的关键技术, 其主要研究难点之一是在低信噪比下, 可用于区分目标与背景噪声的特征少。研究的对象是激光雷达的远距离目标回波, 主要指空中飞机目标。根据试验得到的数据, 发现目标点在背景中往往是一些孤立的点, 与背景的相关性较小。而背景中的任一点与前后背景点相关性较强, 可以用周围的点进行线形或非线性表示。为解决低信噪比下激光雷达的目标检测问题, 提出了基于背景特征参数的目标检测算法。运用高阶统计量作为背景特征值对杂波数据进行处理。在一个小区域内, 背景的高阶统计量不会有很大的起伏, 而目标在它所在的区域内具有相对突出的变化。信噪比得以提高, 然后通过恒虚警检测和多帧相关检测, 获取真正的目标。试验结果表明该方法非常有效, 实时性强, 具有较高的实用价值。     

红外背景抑制与弱小目标的检测算法

强噪声背景下红外图像中弱小目标的检测一直是研究的重点和难点。根据弱小目标、背景干扰和噪声在红外图像中的差异,研究了三种低信噪比条件下红外图像中弱小目标的检测算法:小波变换、数学形态学、Top—hat算子,分别给出了处理的图像和相应的数据。仿真实验表明:这三种检测算法能十分有效地提高信噪比、增强目标、抑制背景杂波和去除噪声干扰,对信噪比约为2的弱小目标检测能得到很好的结果。三种算法所得结果一致,而且处理速度快,适合于实时图像处理和目标探测。     

光子计数激光雷达的时间相关卡尔曼深度估计

在高背景噪声和低积分时间的激光雷达远距离成像场景中,针对传统方法得到的深度图像目标被噪声淹没和深度估计偏差较大的问题,提出了一种基于信号光子时间相关性和自适应卡尔曼滤波器的深度信息估计方法。首先,提取在时间上具有聚集特征的光子计数形成集合;然后,分析了影响信号光子在时间上分布的因素并使用静态高斯线性模型来描述该集合;最后将集合中的所有光子飞行时间乱序,输入改进的自适应卡尔曼滤波器,从而迭代估计深度值。在信号噪声比为1的室内,积分时间分别为10 ms和1 ms时,本文方法相对传统的最大似然方法在均方根误差指标上提升了40%和38%。在信噪比约为0.135的室外2 km目标成像实验中,在信号光子数分别为100、33和17的情况下,本文方法成像效果都优于传统最大似然估计方法和时间相关光子快速去噪方法,得到的深度图像都更清晰,噪声更低。在高噪声和短积分时间下,本文方法可以被运用于激光雷达远距离成像的深度信息估计和图像恢复中。     

Non-uniformity correction of infrared focal plane array in point target surveillance systems

We discuss the influence of non-uniformity and non-uniformity correction on point target detection in infrared surveillance system, and propose a non-uniformity correction approach which is based on signal intensity and sensor characteristics. Theoretical models are used to derive the combined effect of background clutter, sensor random noise, target, non-uniformity and correction error on the signal-to-noise-and-clutter ratio. From our analysis, it can be noted that background clutter intensity is successively modulated by sensor non-uniformity and non-uniformity correction, while sensor random noise is modulated by the non-uniformity correction process only. Furthermore, background clutter and sensor random noise are the key factors that affect the performance of a surveillance system, when it is used to detect point targets. The method presented in this paper takes all of the above into account, moreover, it considers the difference between scanning and staring focal plane array. The experimental results demonstrate the effectiveness of the proposed method.     

Photon-number-resolving detection at 1.04 μm via coincidence frequency upconversion

We demonstrate photon-number-resolving detection based on coincidence frequency upconversion. Pumped by synchronized pulses, the photon signal of the coherent state at 1.04 μm was upconverted into visible replicas with preserved photon number distribution. The upconverted photons were then registered by a silicon multipixel photon counter. The photon-number-resolving performance was improved by reducing the background counts with a synchronous pump as the coincidence gate and reducing the intrinsic parametric fluorescence influence with long-wavelength pumping. A total detection efficiency of 3.7% was achieved with a quite low noise probability per pulse of 0.0002.     

Detection method for small and dim targets from a time series of images observed by a space-based optical detection system

To revisit cataloged space targets, a space-based optical detection system normally observes space targets continuously in a target tracking mode. In the time series of images produced by continuous observation, there are not only the target but also complicated background clutter (a mass of stars) and noises. The existing method only can detect the target with an signal-to-noise ratio (SNR) greater than 6 from these images. This paper presents a detection method for the target with an SNR less than 6. The proposed method consists of an SNR enhancement algorithm and an adaptive background and noise suppression algorithm. Simulation and analytical results show the proposed method detects the target submerged in noise and background clutter when SNR is equal to 3 and the detection probability and the false alarm probability both reach very high performance. This proposed method can help solve the problem of revisiting some weak cataloged space targets.     

Principal curvature for infrared small target detection

Small target detection in infrared image with complex background and low signal–noise ratio is an important and difficult task in the infrared target tracking system. In this paper, a principal curvature-based method is proposed. The principal curvatures of target pixels are negative and their absolute values are larger than that of background pixels and noise pixels in a Gaussian-blurred infrared image. The proposed filter takes a composite function of the curvatures for detection. An approximate model is also built for optimizing the parameters. Experimental results show that the proposed algorithm is effective and adaptable for infrared small target detection in complex background. Compared with several popular methods, the proposed algorithm demonstrates significant improvement on detection performance in terms of the parameters of signal clutter ratio gain, background suppression factor and ROC.     

单矢量水听器稀疏近似最小方差方位估计算法

针对单矢量水听器海上目标探测问题,利用稀疏近似最小方差(Sparse Asymptotic Minimum Variance,SAMV)算法进行目标方位估计,该算法利用单矢量水听器自身具有阵列流形的特点,将整个扫描空间离散化,目标方位分布于某一离散方向位置上,利用空间信号的稀疏性可提高目标方位估计性能。仿真结果表明,SAMV算法在各信噪比条件下方位估计噪声背景级明显优于常规波束形成(Conventional Beam Forming,CBF)算法和最小方差无失真响应(Minimum Variance Distortionless Response,MVDR)算法,当信噪比大于0dB时,该算法测向结果均方根误差小于2°,且SAMV算法具有更好的空间方位分辨能力。消声水池和海上声学浮标海上试验数据处理结果表明,SAMV算法给出了噪声背景级更低的目标方位历程图,有效验证了SAMV算法对海上目标的探测性能及其有效性。      

复杂背景下运动点目标的检测算法

在复杂背景红外序列图像中,运动点目标的检测一直是研究的重点和难点。介绍了一种新的复杂背景下运动点目标的检测算法。首先根据点目标、背景干扰和噪声在红外图像中的差异,运用窗口大小不同的均值滤波器进行背景抑制以提高图像的信噪比,然后用一种门限法得到新的分割序列图像,最后采用改进后的隔帧差分光流场算法可有效地检测出点目标。仿真实验表明该算法优于传统光流场算法,能够检测帧间位移小于一个像元的运动目标,具有较好的检测性能,且实时性强。     

Detection of infrared small target based on fusion of multi-filters北大核心CSCD

Aiming at solving accuracy problem of infrared small target detection in sky and ocean background scenarios of infrared image sequences, a novel infrared small target detection based on multi-filters algorithm fusion method is presented in this paper. Firstly infrared small target and imaging, time and space characteristics of the corresponding background noise are analyzed. Tophat algorithm with improved Robinson guard filter are then integrated to highlight target and suppress clutter background by using infrared small target imaging features. Adaptive threshold segmentation is used to extract candidate targets, while Unger smoothing filter and multi-objects association filter are used to eliminate random noise and false targets in the candidate targets. Multiple experiments of infrared small target image sequences are implemented, and experimental results show that proposed method can detect infrared small targets at 99% detection rate with high reliability and good real-time performance. © 2017, Editorial Board, Journal of Applied Optics. All right reserved.     

Accuracy analysis of centroid calculated by a modified center detection algorithm for Shack-Hartmann wavefront sensor

The accuracy of the Shack-Hartmann wavefront sensor for measuring the wavefront distortion is mainly dependent upon the measuring accuracy of the centroid of each spot. A modified center detection algorithm, which uses some power from the photon events of each pixel instead of photon events themselves, is analyzed theoretically and the computer simulations are given. The results show that photon noise error and sampling error increases as the power value goes up; and to some powers, the readout noise and background noise error decrease. An experiment is described through which the optimum power can be obtained.     

Computer-based photon-counting lock-in for phase detection at the shot-noise limit

We implement a simple computer-based photon-counting lock-in that combines the signal-to-noise benefits of photon counting with lock-in detection. We experimentally specify the flatness and the noise characteristics of a flexible software implementation. The noise of amplitude and phase of the small signal is at the limit of photonic shot noise; from 1000 counted photons we reach an amplitude resolution of 4.5% and a phase resolution of 13 degrees . The photon-counting lock-in reduces illumination noise, detector dark count noise, and can suppress background. In particular, phase detection is useful to image the delay characteristics in microscopic systems by use of fluorescent probes that are designed to report membrane potential, temperature, or concentration in a chemical reaction.     

Performance parameters for detection in low-flux coherent images

We analyze the optimization of low-flux coherent active imagery systems for target detection. We demonstrate that, unlike the Fisher ratio, the Bhattacharyya distance is an efficient figure of merit when one uses detection algorithms based on the generalized likelihood ratio test for realistic situations when the target and the background mean values are unknown. For example, we show that detection capabilities can be better if the pulse energy is divided into four shots, whereas using more than ten shots does not significantly improve the results.     

Detection efficiency enhancement of single-photon detector at 1.55-μm by using of single photons lock-in and optimal threshold

The detection efficiency considerations are often the true determining factor as to whether a sensitive measurement is feasible. We demonstrate a robust method of single photons lock-in to enhance the detection efficiency of InGaAs single-photon avalanche diodes at 1.55-μm wavelength and suppressing background noise. With the optimal threshold for discrimination, the detection efficiency is achieved to 1.87 times bigger than that of the conventional photon counting method.     

Hybrid multi-resolution detection of moving targets in infrared imagery

A hybrid moving target detection approach in multi-resolution framework for thermal infrared imagery is presented. Background subtraction and optical flow methods are widely used to detect moving targets. However, each method has some pros and cons which limits the performance. Conventional background subtraction is affected by dynamic noise and partial extraction of targets. Fast independent component analysis based background subtraction is efficient for target detection in infrared image sequences; however the noise increases for small targets. Well known motion detection method is optical flow. Still the method produces partial detection for low textured images and also computationally expensive due to gradient calculation for each pixel location. The synergistic approach of conventional background subtraction, fast independent component analysis and optical flow methods at different resolutions provide promising detection of targets with reduced time complexity. The dynamic background noise is compensated by the background update. The methodology is validated with benchmark infrared image datasets as well as experimentally generated infrared image sequences of moving targets in the field under various conditions of varying illumination, ambience temperature and the distance of the target from the sensor location. The significant value of F-measure validates the efficiency of the proposed methodology with high confidence of detection and low false alarms.     

Design and performance evaluation of the imaging payload for a remote sensing satellite

In this paper an analysis method and corresponding analytical tools for design of the experimental imaging payload (IMPL) of a remote sensing satellite (SINA-1) are presented. We begin with top-level customer system performance requirements and constraints and derive the critical system and component parameters, then analyze imaging payload performance until a preliminary design that meets customer requirements. We consider system parameters and components composing the image chain for imaging payload system which includes aperture, focal length, field of view, image plane dimensions, pixel dimensions, detection quantum efficiency, and optical filter requirements. The performance analysis is accomplished by calculating the imaging payload's SNR (signal-to-noise ratio), and imaging resolution. The noise components include photon noise due to signal scene and atmospheric background, cold shield, out-of-band optical filter leakage and electronic noise. System resolution is simulated through cascaded modulation transfer functions (MTFs) and includes effects due to optics, image sampling, and system motion. Calculations results for the SINA-1 satellite are also presented.