Modified spin filter for noise reduction in aerodynamic imaging

A new filtering algorithm was developed for the removal of random noise from digitally imaged aerodynamic flow structures while minimizing geometrical distortion of their shapes. This is a modification of a spin filter previously presented. The algorithm defines a kernel around each pixel and detects the direction of the prevailing pattern passing through that kernel. The median grey level along this preferred direction is then used to replace the grey level recorded by the pixel at the centre of the kernel. Applications of this filter were demonstrated by processing shadowgraph images of shock waves. The noise as measured by the standard deviation from the mean was reduced by nearly 50% after one application of the filter and by nearly 70% after three applications, while distortion of the imaged shock angle remained below the angle measurement uncertainty.     

Numerical and experimental study on coherent beam combining of fibre amplifiers using simulated annealing algorithm

We present the numerical and experimental study on the coherent beam combining of fibre amplifiers by means of simulated annealing (SA) algorithm. The feasibility is validated by the Monte Carlo simulation of correcting static phase distortion using SA algorithm. The performance of SA algorithm under time-varying phase noise is numerically studied by dynamic simulation. It is revealed that the influence of phase noise on the performance of SA algorithm gets stronger with an increase in amplitude or frequency of phase noise; and the laser array that contains more lasers will be more affected from phase noise. The performance of SA algorithm for coherent beam combining is also compared with a widely used stochastic optimization algorithm, i.e., the stochastic parallel gradient descent (SPGD) algorithm. In a proof-of-concept experiment we demonstrate the coherent beam combining of two 1083~nm fibre amplifiers with a total output power of 12~W and 93% combining efficiency. The contrast of the far-field coherently combined beam profiles is calculated to be as high as 95%.     

高功率激光器自动准直系统图像处理的可信度评估

自动准直系统是将采集的图像进行特定算法处理获取光束的位置信息,驱动电机调整光斑到指定的位置,其中图像质量对光束定位的精确性影响很大,为尽量避免受严重噪音和光束畸变影响的图像进入图像处理流程而产生准直结果的错误判断,保证自动准直系统图像处理结果的精确性,试图提供一种较为简单的判断依据,采用基于Monte-Carlo模拟方法,建立了远场准直过程中三种主要噪音的干扰评估模型,以测量不确定度作为定量判断处理图像与否的特征参数,将该结果做成统计图表作为判断依据。结果表明,在设定合理测量不确定度阈值的情况下,该特征参数能够较好地排除不良图像,从而提高准直结果的可信度。     

Infrared target tracking in multiple feature pseudo-color image with kernel density estimation

Tracking targets in infrared images is a challenging subject due to the low contrast and severe noise. Kernel density estimation (KDE) with robust performance is one of the well-known tracking algorithms. In essence, tracking targets with KDE algorithm is tracking the statistical features of their pixels by the histograms. The universal KDE which can track any features of targets has not been developed. We propose a strategy which does not need to improve on the KDE algorithm itself, but it can make KDE track other features. We first map the features into the pixel intensity and create the feature images. Then these feature images are used to construct the multiple feature pseudo-color images (MFPCIs). The kernel density estimation algorithm tracks targets in MFPCIs can indirectly track these features. Experiments validate that the performance of tracking targets in MFPCIs outperforms that of tracking them in the original infrared images.     

Optimized microphone deployment for near-field acoustic holography: To be, or not to be random, that is the question

Arrays with sparse and random sensor deployment are known to be capable of delivering high quality far-field images without grating lobes. This raises the question of whether or not this idea can be applied to near-field imaging as well. To answer this question that has not yet been widely investigated in previous research, numerical simulations are undertaken in this paper to optimize the microphone deployment for both far-field and near-field arrays with the latter being the main focus. In the simulation, a recently introduced near-field equivalent source imaging (NESI) technique is employed for the near-field imaging. Global optimization techniques including the simulated annealing (SA) algorithm and the intra-block Monte Carlo (IBMC) algorithm are exploited to find the optimal microphone position efficiently. The combined use of the SA and the IBMC algorithms enables efficient search for satisfactory deployment with excellent beam pattern and relatively uniform distribution of microphones. In the near-field optimization, a special kind of beam pattern and cost function definition is used for the multiple-input-multiple-output (MIMO) imaging problem. As indicated by the simulation results, random deployment of microphones is necessary to avoid grating lobes in far-field imaging. In the near-field simulation, all results suggest that the optimal near-field array is the uniform rectangular array (URA) and the random deployment presents no particular benefit in near-field imaging.     

基于改进开关中值滤波的多孔网栅图像脉冲噪声消除

针对多孔网栅闪光照相图像含有随机脉冲噪声的问题,提出了一种改进的开关中值滤波噪声消除算法。该算法利用像素与邻域窗口统计中值的灰度信息,建立噪声点探测器。通过设置噪声点探测阈值来识别噪声,并用邻域窗口内统计中值代替噪声点取值。经过多次滤波,含随机脉冲噪声的计算机合成网栅图像及实验网栅图像可获得良好的恢复效果。     

基于高斯马尔科夫模型的高光谱异常目标检测算法研究

随着光谱成像技术的发展,高光谱异常检测在遥感图像处理中的应用越来越广泛。传统RX异常检测算法忽略影像空间相关性,而且由于没有经过有效数据降维,运算耗费大,对于高光谱数据有效性不高。高光谱影像在空间和光谱上符合高斯-马尔科夫模型。通过建立马尔科夫参数能够直接计算协方差矩阵的逆矩阵,避免了高光谱海量数据的庞大计算。提出一种基于三维高斯-马尔科夫随机场模型的改进RX异常检测算法。该方法用高斯-马尔科夫随机场模型模拟高光谱影像数据,用最大似然近似法估计高斯-马尔科夫随机场参数,由高斯-马尔科夫随机场参数直接构造检测算子,并以待检测像元为中心设置局部优化窗口,称为马尔科夫检测窗。取窗口内数据计算均值向量和协方差逆矩阵,得到中心像元的异常度,通过移动窗口进行逐像元检测。应用AVIRIS高光谱数据对传统RX算法、高斯-马尔科夫模型背景假设异常检测算法和该算法进行了仿真实验对比。结果表明,该算法能够有效提高高光谱异常检测效率,降低虚警率。运行时间较传统RX算法提高了45.2%,体现出更好的计算效率。     

基于并行梯度下降算法模拟高功率固体激光装置的相干合成

 多路光的相干合成是高功率固体激光装置的关键技术之一。基于合成模型,对4组tilt/tip-piston镜采用并行梯度算法,通过模拟计算实现了光束间的位相锁定和相干合成。结果表明有限次算法迭代次数内,相干合成时远场焦斑10 μm半径范围内的强度比约为非相干合成时的4倍。基于高频响应驱动器和对应的高速控制算法将有可能实现高功率固体激光装置多路输出光束间的相干合成。     

Two sub-pixel processing algorithms for high accuracy particle centre estimation in low seeding density particle image velocimetry

This article presents two algorithms for spatial processing of low seeding density PIV (particle image velocimetry) images which lead to sub-pixel precision in particle positioning. The particle centres are estimated to accuracies of the order of 0.1 pixel, yielding 1% error in velocity calculation. The first algorithm discriminates valid particles from the rest of the image and determines their centres in Cartesian coordinates by using a two-dimensional Gaussian fit. The second algorithm performs local correlation between particle pairs and determines instantaneous two-dimensional velocities. The methods have been applied initially to simulated data. Gaussian noise and distortion has then been added to simulate experimental conditions. It is shown that, in comparison with conventional methods, the new algorithms offer up to an order of magnitude higher accuracy for particle centre estimation. Finally, the Gaussian fit approach has been used to map an experimental transonic flow field from the stator trailing edge wake region of a cascade with an estimated error of 1%. The experimental results are found to be in good agreement with previous theoretical steady-state viscous calculations.     

随机高斯型相位板的束匀滑特性

 针对激光系统对光束匀滑的需求,设计了高斯型连续相位板,并对其远场特性进行了研究。分别计算了相干长度为39,30,10和3 mm的高斯相位板远场光斑分布,结果显示相位板自身相关长度是决定远场能量分布的重要因素,当相干长度大于10 mm时,由于不满足各态历经条件,远场光斑分布能量分散。当相干长度小于10 mm后,由于满足各态历经条件,远场光斑能量将接近理想的高斯分布特性。通过数值计算模拟了相干长度为3 mm的连续相位板对畸变光束进行匀滑处理的过程,演示了束匀滑处理结果。通过比较匀滑前后远场光斑的能量分布,显示了畸变光束通过连续相位板后远场光斑能量分布变化情况,通过相位板后,光斑形状明显接近理想高斯分布情况。     

基于小波变换的红外热波无损检测融合算法

在红外热波无损检测中获取的热像序列存在着背景噪声大、缺陷边缘模糊、对比度低等特点。为了提高由红外热像序列重构的数字图像的缺陷显示能力,以小波变换为热像处理工具,采用基于像素级和特征级的图像融合算法对热像序列进行了处理,并采用基于统计学的图像评估标准对处理效果作了定量评价。通过对铝合金试件的检测实验说明该方法可用于材料内部缺陷的红外热波无损检测。研究结果表明,此种图像融合算法可对不同深度缺陷所对应的两幅最佳热像进行有效地融合,在一幅融合图像中直观地反映出全部缺陷,并能有效地减少加热不均和背景噪声对缺陷识别的不利影响。     

强激光远场光斑强度分布测量技术

准确测量激光远场光斑强度时空分布是分析强激光大气传输效应和评价激光系统性能的有效手段。概述了测量激光光斑强度分布的几种方法及其适用性,重点叙述了基于阵列探测法的强激光远场光斑强度分布测量技术,总结分析了量热阵列法、光电阵列法和量热/光电复合法等三类阵列探测系统应用特点。最后介绍了两种分别用于测量连续波高能激光和重频脉冲激光的光电阵列靶斑仪,系统具有结构紧凑的特点,能够满足运动靶目标上强激光参数测量要求。     

Improving spatio-temporal resolution of infrared images to detect thermal activity of defect at the surface of inorganic glass

This paper proposes a noise suppression methodology to improve the spatio-temporal resolution of infrared images. The methodology is divided in two steps. The first one consists in removing the noise from the temporal signal at each pixel. Three basic temporal filters are considered for this purpose: average filter, cost function minimization (FIT) and short time Fast Fourier Transform approach (STFFT). But while this step effectively reduces the temporal signal noise at each pixel, the infrared images may still appear noisy. This is due to a random distribution of a residual offset value of pixels signal. Hence in the second step, the residual offset is identified by considering thermal images for which no mechanical loading is applied. In this case, the temperature variation field is homogeneous and the value of temperature variation at each pixel is theoretically equal to zero. The method is first tested on synthetic images built from infrared computer-generated images combined with experimental noise. The results demonstrate that this approach permits to keep the spatial resolution of infrared images equal to 1 pixel. The methodology is then applied to characterize thermal activity of a defect at the surface of inorganic glass submitted to cyclic mechanical loading. The three basic temporal filters are quantitatively compared and contrasted. Results obtained demonstrate that, contrarily to a basic spatio-temporal approach, the denoising method proposed is suitable to characterize low thermal activity combined to strong spatial gradients induced by cyclic heterogeneous deformations.     

Optimized K-means (OKM) clustering algorithm for image segmentation

This paper presents the optimized K-means (OKM) algorithm that can homogenously segment an image into regions of interest with the capability of avoiding the dead centre and trapped centre at local minima phenomena. Despite the fact that the previous improvements of the conventional K-means (KM) algorithm could significantly reduce or avoid the former problem, the latter problem could only be avoided by those algorithms, if an appropriate initial value is assigned to all clusters. In this study the modification on the hard membership concept as employed by the conventional KM algorithm is considered. As the process of a pixel is assigned to its associate cluster, if the pixel has equal distance to two or more adjacent cluster centres, the pixel will be assigned to the cluster with null (e. g., no members) or to the cluster with a lower fitness value. The qualitative and quantitative analyses have been performed to investigate the robustness of the proposed algorithm. It is concluded that from the experimental results, the new approach is effective to avoid dead centre and trapped centre at local minima which leads to producing better and more homogenous segmented images.     

Iterative block level principal component averaging medical image fusion

Image fusion is a method of integrating all relevant and complementary information from images of same source or various sources into a single composite image without any degradation. In this paper, a novel pixel level fusion called Iterative block level principal component averaging fusion is proposed by dividing source images into smaller blocks, thus principal components are calculated for relevant block of source images. Average of principal components of all the blocks provide weights for fusion rule, thus importance is given to blocks of source images. In this scenario, Iterations are incorporated in the form of size of blocks of source images which gives fusion results with maximum average mutual information. This algorithm is experimented for the fusion of noise free medical images and noise filtered of the same. The experimental results for both the cases show that the proposed algorithm performs well in terms of average mutual information and mean structural similarity index.     

子束排列方式对固体激光器光束合成特性的影响

 建立了固体激光器矩形光斑光束合成的理论模型,对诺·格公司给出的2束、4束、8束合成实验结果进行分析,并通过数值模拟,得到了不同子束排列方式下合成光斑的远场图形。通过仿真模拟可以得出:排列结构影响远场光斑的形状;子束间距决定了合成光束远场光斑的衍射旁瓣的大小和多少。采用环围能量进行分析,研究了远场光斑中主瓣能量随激光阵列占空比的变化。结果显示,远场光束环围功率随子束间距的增大而逐渐下降,而且参与相干合成子束越多,下降越大。     

基于纹理显著性的微光图像目标检测

微光图像对比度较低,目标显著性不明显,目标自动探测难度大.针对此问题,本文提出一种噪声鲁棒性较好的图像局部纹理粗糙度算法,并给出一种适用于微光图像显著分析的纹理显著性算法.首先,提出一种新的局部纹理粗糙度算法,该算法利用最佳尺寸计算局部纹理粗糙度,对纹理图像进行加噪实验,与基于局部分形维的粗糙度方法相比,本文局部纹理粗糙度算法表现出较好的噪声鲁棒性;其次,在提取图像粗糙度特征图的基础上,给出一种针对纹理的显著性度量算法;最后,将纹理显著性算法应用于微光图像目标检测,实验结果证明了该算法的有效性.     

Far-field spot compression without energy loss in main lob in wireless laser communication

Far-field spot compression without energy loss in main lob is of great significance to wireless laser communication. In this letter, we propose two schemes to obtain far-field spot compression without energy loss in main lob. One scheme is based on the simulated annealing (SA) algorithm. Using SA algorithm, we design the phase profile of the diffractive phase element (DPE). Using the designed DPE, far-field spot compression without energy loss in main lob is achieved. The other scheme is based on YG algorithm. By means of YG algorithm, we appropriately designed the DPE in the emitting plane. Using the DPE, far-field spot compression without energy loss in main lob is obtained.     

An ensemble template algorithm for extracting targets from blurred infrared images

In this paper, an ensemble template algorithm is proposed to extract targets from blurred infrared images. First, the image pixels are divided according to their gray values into three pixel sets, a target set, a background set and the third set without class label. Second, the neighborhood statistical characteristics for each pixel are calculated as its template features. Third, ensemble detectors are designed using target pixels and background pixels based on their template features, and these ensemble detectors are used to detect the third pixel set. To evaluate the performance of the proposed extraction algorithm, this paper compares the ensemble template with other extraction algorithms using blurred infrared image of hand trace. Experimental results show that the ensemble template algorithm proposed in this paper exhibits better extraction performance.     

一种快速检测圆心的抗噪声亚像素算法

在印刷电路板的自动光学检测中，被检对象的空间对准是一个关键步骤，而传统的图像匹配技术由于其只能在像素级定位，而无法适应印刷电路板精确对准的要求。本文利用圆的几何对称性，提出一种在亚像素精度快速定位圆心的算法。