时空过采样探测系统性能仿真

基于星载扫描辐射计的工作原理,对传统的线列扫描成像系统和过采样系统的采样过程进行了数学建模和仿真成像,在两种采样模式下对点目标探测进行了仿真。在Matlab环境下对过采样探测系统进行了仿真图像的沿线阵方向的两倍空间过采样和扫描方向上（即时间上）的2~10倍的过采样仿真。通过对过采样探测系统各种工况下的仿真,得到了图像中信号能量值和目标尺寸大小的关系,分析了目标位置的不同对成像质量造成的影响。最后给出了不同大小目标两个通道上的四倍过采样图像,并分析了图像中存在的跨像元现象。     

显微热成像系统自适应位置标定方法

利用光学微扫描技术,可在不改变探测器结构的情况下,提高显微热成像系统空间分辨率。但为了获得高质量过采样重构图像,微扫描位置需要标定。基于零点定标,提出一种各点自适应定标的微扫描位置标定方法。模拟实际系统在定标前后的欠采样图像,采用不同重构方法进行仿真对比验证;完成了实际采集的欠采样显微热图像序列的重构对比实验。实验结果表明该方法明显改善了显微热成像系统的过采样重构图像质量,提高了系统空间分辨率。此方法还可以应用在其他光电成像系统中。     

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.     

Infrared dim small target enhancement using toggle contrast operator

A new infrared dim small target enhancement algorithm based on toggle contrast operator is proposed. Toggle contrast operator is modified and used to construct operators using the image features derived from dilation and erosion operators. Then, based on the constructed operators, the operators which could be used to estimate the clutter background of the original infrared dim small target image are proposed using the same strategy as the definition of opening. Finally, the infrared dim small target is well enhanced through subtracting the estimated background from the original image. Experimental results on infrared images with different types of targets verified that the proposed method could effectively enhance infrared dim small target, which would be very useful for infrared dim small target detection and tracking.     

基于多帧背景的泄漏气体自适应匹配滤波检测

被动傅里叶变换红外(FTIR)扫描遥测成像系统采集的红外高光谱图像具有空间、光谱等维度信息,可被用于大气环境中有毒有害气体的识别、定量及可视化。该系统具有光谱分辨率高、非接触式及远距离探测等优点,然而其单帧图像的像元数量少且部分存在气体吸收或发射特征,无法直接用于红外高光谱图像的目标检测。提出了基于多帧背景的泄漏气体自适应匹配滤波(AMF)检测方法,以短时间内、同一区域的多帧红外高光谱图像为基础,筛选出无目标气体特征的背景光谱并计算探测区域的背景最大似然估计,应用于后续帧的目标气体泄漏检测。红外高光谱图像来自于SF₆气体的遥测实验,共扫描四帧（120像元/帧）,去除前三帧内含有目标气体特征的像元光谱,剩余背景光谱被用于计算背景的最大似然估计,第四帧红外高光谱图像逐像元对SF₆气体进行的AMF检测,并与非线性最小二乘法反演的SF₆柱浓度图像比对,结果表明AMF检测高值与柱浓度高值有较强的相关性。为验证多帧背景在不同空间检测方法下的性能,分别对该帧数据进行了基于正交子空间的自适应子空间检测(ASD)、基于混合空间的自适应余弦检测(ACE)及基于斜子空间的最大似然比检测(OGLRT),并分别与SF₆柱浓度图像比对,结果表明多帧背景适用于不同空间的检测方法。此外,为验证存在目标气体吸收特征的非背景光谱对背景空间的影响,向背景空间中加入多条含有SF₆气体吸收特征的光谱,通过ROC曲线检验,结果表明背景空间中混入目标气体特征会降低AMF方法的检测性能。AMF检测值的假彩色图像也能应用于被动FTIR扫描遥测成像系统,相较于柱浓度假彩色图像,泄漏源及扩散趋势更为明显。基于红外高光谱图像的检测方法依赖于整体背景的统计特性,相较于单像元光谱波段的反演算法,极大地降低了背景的依赖性。多帧背景下的AMF泄漏气体检测方法能很好地应用于被动FTIR扫描遥测成像系统上并满足在线监测要求。     

基于数学形态学的弱点状运动目标的检测

提出了一种新的基于数学形态学的红外图像序列中弱点状运动目标的非参数检测算法。采用数学形态学抑制背景杂波干扰和增强目标,用沿时间轴投影和二维空域搜索代替复杂的时空三维搜索形成组合帧,然后在每条可能的轨迹上将进行目标能量累加,实现了一种快速检测前跟踪(TBD)检测算法。仿真实验表明:在恒虚警概率条件下,该检测算法能高效地检测信噪比约为2的弱点状运动目标,检测性能对噪声分布不敏感,能精确地得到目标的即时位置和速度信息,适合于实时图像处理和目标探测,具有很高的实用价值。     

预警卫星半实物仿真系统设计与实现

国防支援计划(DSP)是美国现役的预警卫星系统,主要对导弹进行早期探测和预警。为评估DSP卫星对目标的探测能力,文中分析了预警卫星的部署情况和工作模式,提出了预警卫星仿真系统的总体设计方案,确定该系统的功能模块以及实现方式;根据预警卫星双波段探测的工作模式构建了红外双色扫描探测模型,提出了基于双霍夫变换的多帧关联目标检测算法,利用目标的运行特性有效去除背景噪声,并结合双波段探测信息融合策略降低卫星虚警率,最后利用双星定位方法预估目标轨迹并对不同发射角目标的预测轨迹与真实轨迹之间的误差进行对比分析。通过试验运行,该系统达到了预期结果,具备对目标导弹的探测和跟踪能力,为导弹性能评估提供一种仿真手段和依据。     

A robust infrared dim target detection method based on template filtering and saliency extraction

Dim target detection in infrared image with complex background and low signal-clutter ratio (SCR) is a significant and difficult task in the infrared target tracking system. A robust infrared dim target detection method based on template filtering and saliency extraction is proposed in this paper. The weighted gray map is obtained from the infrared image to highlight the target which is brighter than its neighbors and has weak correlation with its background. The target saliency map is then calculated by phase spectrum of Fourier Transform, so that the dim target detection could be converted to salient region extraction. The potential targets are finally extracted by combining the two maps. Moreover, position discrimination between targets in the two maps is used to exclude the false alarms and extract the targets. Experimental results on measured images indicate that our method is feasible, adaptable and robust in different backgrounds. The ROC (Receiver Operating Characteristic) curves obtained from the simulated images demonstrate the proposed method outperforms some existing typical methods in both detection rate and false alarm rate, for target detection with low SCR.     

基于分块速度域改进迭代运动目标检测算法的红外弱小目标检测

提出一种基于分块速度域的迭代红外运动目标检测算法来解决传统算法计算量巨大这一难题.首先,采用二维最小均方差滤波器对红外序列图像进行滤波,获得包含弱小目标以及残差的红外序列图像.然后,通过在序列图像块的速度域上应用改进的迭代运动目标检测算法进行能量累积,从而将弱小目标的运动速度在速度域进行累积增强,达到检测弱小运动目标的目的.最后在解算出的速度值附近进行搜索,得到弱小目标运动的精确速度.利用此速度进行空域能量累积,得到叠加图像,在此图上进行目标检测.与传统方法相比较,几组实验结果显示,本文提出的方法大大缩短了检测的时间,而且本文方法的检测效果也较好.     

相干X射线衍射成像的数字模拟研究

相位重建是实现X 射线相干衍射成像的关键, 它利用远场采集的样品傅里叶相干衍射花样、结合过采样理论,再采用迭代算法复原样品的相位信息. 文中采用数字模拟的方法, 利用小尺寸二维非周期性图形作为物场, 研究了过采样比对重构结果的影响, 研究发现, 迭代次数为1000 次时最佳过采样比的范围是3—7 之间. 利用噪声模拟方法, 研究了噪声对相位重建的影响, 找到了完成相位重建的噪声限是信噪比不能低于10. 分析了重构结果中孪生像以及随机平移的产生原因, 并给出了相应的解决办法, 结果表明, 此方法可有效地提高重构图像的质量. 关键词： 相干X射线衍射成像 过采样 相位重建算法 显微成像     

An improved infrared dim and small target detection algorithm based on the contrast mechanism of human visual system

To achieve higher detection rate and lower false alarm rate in dim and small target detection, this paper proposed an improved algorithm based on the contrast mechanism of human visual system (HVS) for infrared small target detection in an image with complicated background. According to the contrast mechanism of HVS, Laplacian of Gaussian (LoG) filter is exploited to deal with the input image, which can not only suppress the background noise and clutter but also enhances the target intensity significantly. As a result it increases the contrast ratio between target and background. To further eliminate residual clutter, we process the filtered image with morphological method in all directions. True target is finally obtained by applying local thresholding segmentation to the pre-processed image. Experimental results demonstrate its superior and reliable detection performance by high detection rate and low false alarm rate.     

基于PDE的前视红外成像舰船目标检测

针对复杂环境下的海面目标提取问题,提出一种基于偏微分方程（PDE）的红外舰船检测算法。首先采用基于PDE理论的滤波模型对初始图像滤噪并进行背景估计,然后结合邻域差分进行背景抑制后分割提取目标。实验表明,该算法能够有效检测强杂波背景中的目标,方法适应性强。     

An improved POCS super-resolution infrared image reconstruction algorithm based on visual mechanism

The traditional projection onto convex sets (POCS) super-resolution (SR) reconstruction algorithm can only get reconstructed images with poor contrast, low signal-to-noise ratio and blurring edges. In order to solve the above disadvantages, an improved POCS SR infrared image reconstruction algorithm based on visual mechanism is proposed, which introduces data consistency constraint with variable correction thresholds to highlight the target edges and filter out background noises; further, the algorithm introduces contrast constraint considering the resolving ability of human eyes into the traditional algorithm, enhancing the contrast of the image reconstructed adaptively. The experimental results show that the improved POCS algorithm can acquire high quality infrared images whose contrast, average gradient and peak signal to noise ratio are improved many times compared with traditional algorithm.     

Morphological center operator for enhancing small target obtained by infrared imaging sensor

Infrared small target in image obtained by infrared imaging sensor is usually different from the surrounding regions, which is the important region in infrared image for different applications. However, the infrared small target is dim and embedded in clutter background, which makes the small target difficult to be detected or recognized. So, it is important to enhance infrared small target. Morphological center operator could smooth important image features, which may be well used for infrared small target enhancement. To well enhance infrared small target, a morphological center operator based method is proposed. The morphological center operator is specified to suppress most of the background of the infrared image through the strategy of feature extraction. Then, the infrared small target is well enhanced. Experimental results show that, the proposed method performs well for enhancing infrared small target and the performance is better than some other methods. So, the proposed method could further improve the performance of infrared imaging sensor.     

多元探测器在玫瑰扫描红外亚成像系统中的应用

玫瑰扫描红外亚成像系统是利用玫瑰扫描机构和红外单元探测器构成的一种亚成像系统。提出了一种利用多元小面阵来替代单元探测器的红外亚成像系统 ,可以提高成像系统的空间分辨率和帧频。分析了系统的原理 ,并给出了系统的构成框图。此外 ,就玫瑰扫描成像系统中应用多元探测器可能出现的问题进行了讨论 ,并提出了解决方案。结果表明 ,这种多元小面阵玫瑰扫描成像系统的成本远低于焦平面阵列探测器红外成像系统 ,在性能改善后是诸如末制导炮弹等低成本应用场合的理想红外成像系统     

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.     

真空条件下低温红外辐射测量技术研究

针对红外载荷在轨服役期间低温目标的红外辐射探测需求，提出一种真空条件下的低温红外辐射测量方案，并研制了测量装置。测量装置主要由低温红外光学系统、低温机械结构、低温红外探测系统及微弱信号处理系统构成。低温红外辐射经过光学系统会聚到探测器像面，锁相放大器利用相干检测技术将目标信号提取，完成低温红外辐射的测量。测量装置研制完成后，在真空仓内使用标准黑体辐射源，在198 K～423 K温度范围内进行了低温红外辐射定标试验，取得了有效的试验数据，测量不确定度在5%以内。该文提出的真空条件下低温红外辐射测量技术可为在轨空间红外载荷低温红外目标探测设计提供重要数据支撑。     

Single infrared image super-resolution combining non-local means with kernel regression

In many infrared imaging systems, the focal plane array is not sufficient dense to adequately sample the scene with the desired field of view. Therefore, there are not enough high frequency details in the infrared image generally. Super-resolution (SR) technology can be used to increase the resolution of low-resolution (LR) infrared image. In this paper, a novel super-resolution algorithm is proposed based on non-local means (NLM) and steering kernel regression (SKR). Based on that there are a large number of similar patches within an infrared image, NLM method can abstract the non-local similarity information and then the value of high-resolution (HR) pixel can be estimated. SKR method is derived based on the local smoothness of the natural images. In this paper the SKR is used to give the regularization term which can restrict the image noise and protect image edges. The estimated SR image is obtained by minimizing a cost function. In the experiments the proposed algorithm is compared with state-of-the-art algorithms. The comparison results show that the proposed method is robust to the noise and it can restore higher quality image both in quantitative term and visual effect.     

Indirect target detection method in FLIR image sequences

Due to the complexity of the scene, target detection in forward-looking infrared (FLIR) imagery is a challenging problem, especially for occluded target. The main contribution of this paper is to propose an indirect detection method for improving the recognition probability and effectiveness of target detection method in FLIR image sequences under complex conditions. The proposed method mainly includes four steps: preparation of forward-looking reference image of landmark, extraction of the real-time scene image, template matching and target location, in which some key technologies are proposed, such as perspective transformation used to solve projective problems, position prediction for improving real-time performance, and target location used for identifying the target’s position. Experimental results are shown to demonstrate the robustness and efficiency of proposed method in FLIR image sequences.     

Feature-based fusion of infrared and visible dynamic images using target detection

We employ the target detection to improve the performance of the feature-based fusion of infrared and visible dynamic images, which forms a novel fusion scheme. First, the target detection is used to segment the source image sequences into target and background regions. Then, the dual-tree complex wavelet transform (DT-CWT) is proposed to decompose all the source image sequences. Different fusion rules are applied respectively in target and background regions to preserve the target information as much as possible. Real world infrared and visible image sequences are used to validate the performance of the proposed novel scheme. Compared with the previous fusion approaches of image sequences, the improvements of shift invariance, temporal stability and consistency, and computation cost are all ensured.