改进的极化SAR点散射目标扰动滤波检测方法

为完成极化合成孔径雷达(PolSAR)图像中点散射像素目标的检测,从几何扰动滤波检测点散射像素的基本原理出发,分析了经典方法存在的相干度参数阈值无法自适应获取和不同散射机制共享同一阈值两个问题,提出利用Cloude-Pottier分解结果中熵参数的分布情况计算得到阈值,利用平均阿尔法角参数完成不同散射机制的初分类,对初分类的结果排序得到的某种散射机制对应的相干度参数的比例因子,根据比例因子计算得到该类散射机制的阈值,从而完成点散射目标的检测。对机载合成孔径雷达（AIRSAR）数据集中的San Francisco Bay图像进行了实验,结果表明,改进方法在检测性能上优于经典方法。     

PolSAR成像的固定极化干扰机有源诱饵目标鉴别及抑制

针对合成孔径雷达(Synthetic Aperture Radar,SAR)成像中真假目标难以区分的问题,提出了一种极化合成孔径雷达(Polarmetric SAR,PolSAR)成像固定极化转发式干扰诱饵目标鉴别方法。该方法首先通过极化熵对目标进行分类,提取低极化熵的目标并对目标进行Wigner-Ville分布(Wigner-Ville Distribution,WVD)变换,再利用Hough变换计算WVD图像中的曲线斜率,将计算出的多普勒调频率与理论调频率进行对比,进而完成真实目标与假目标的鉴别,最终通过极化对消对鉴别出的目标进行抑制。实验结果验证了该方法的有效性。     

极化SAR数据的细节保持分割

提出一种保持场景局部细节的极化合成孔径雷达数据非监督分割方法.该方法将传统的基于极化目标分解的极化SAR分类方法与基于马尔可夫随机场的分类方法相结合,利用迭代条件模型方法得到分割结果.为保持细节特征,同时又能对各向同性区域进行平滑,利用总功率(span)图像的场景均匀性对分类结果进行修正.实验结果表明,与已有方法相比,该方法在细节保持方面有一定改进.     

基于不可分离MRA的快速小波去噪图像重建

提出了一种基于不可分离MRA的小波去噪重建算法.算法将投影数据进行二通道的小波分解,从而直接得到小波的近似系数和细节系数,对这些小波系数进行基于小波的阀值化去噪处理,再经过逆小波变换就得到了最终的重建图像.算法降低了复杂度,与可分离MRA重建算法比较速度更快,并且可以去噪.     

基于稀疏编码的鲁棒型人脸超分辨率重建

为了减少人脸超分图像的边缘伪影和图像噪点，利用基于稀疏编码的单幅图像超分辨率重建算法，在字典学习阶段，结合L1范数引入在线字典学习方法，使字典根据当前输入图像块和上次迭代生成的字典逐列更新，得到更加精确的超完备字典对，用于图像重建。实验中进行的仿真结果表明，改进算法超分结果的峰值信噪比（PSNR）和结构相似性（SSIM）比同类型的稀疏编码超分法（SCSR）和应用在线字典学习算法的超分方法（ODLSR）均有较大幅度提升，比后者平均提升0.72 dB和0.018 7。同时，视觉上有效地消除了边缘伪影，且在处理含噪人脸图像时，具备更强的去噪能力和更好的鲁棒性。     

瞬变电磁信号去噪方法及效果研究

采样后的瞬变电磁信号数据容易受到各种噪声的干扰，造成数据处理时分辨率较低，进而出现异常解释信息，影响后续工作进程．因此，必须选日蛤适的方法对其进行去噪处理。本文集中对三点指数逼近非线}生平滑去噪、基于小波闽值的信号去噪、基于小波变换模极大值的信号去噪、基于小波包的信号去噪等方法及效呆进行比较，对瞬变电磁法的去噪工作具有一定的现实意义。     

一种基于卷积运算与全变分模型的图像去噪方法

梯度模值较易受到外界影响，导致全变分模型在大噪声点处往往不能很好地消除噪声，从而产生阶梯效应。针对该问题，提出了一种基于卷积运算与全变分模型的图像去噪方法。首先，针对以扩散形式获得的图像像素点进行卷积运算，利用滤波去噪降低大噪声点的灰度值；其次，以能量泛函形式构建图像全变分模型，并求解泛函对应的拉格朗日方程极小值来实现图像去噪；最后，将去噪后图像作为双边滤波算法的引导图像进行二次去噪，从而进一步提升图像去噪质量。仿真实验结果表明，与经典方法相比，该模型对去噪过程中的阶梯效应问题具有较好的处理效果。     

利用生成对抗网络的时频图像去噪和增强处理

针对雷达信号时频图像的去噪和增强问题，提出了利用生成对抗网络二次生成时频图像的方法。首先利用时频分析产生雷达信号的时频图像作为原始数据集1;接着利用生成对抗网络对数据集1进行学习之后生成新的数据集2，数据集2相对于数据集1拥有着去噪和增强的效果;最后提取时频图像奇异值特征检验生成的数据集2的有效性。对6种常见的雷达信号的时频图像进行了仿真实验，结果证明了该方法在时频图像去噪和增加样本多样性方面是有效的。     

基于多测量向量模型的极化探地雷达成像算法

针对极化探地雷达(GPR)工作过程中目标成像空间的联合稀疏性，提出了一种基于多测量向量模型的极化探地雷达成像算法。在建立极化探地雷达回波信号模型的基础上，利用各极化通道测量数据的联合稀疏性将各个极化通道的测量数据等效成多测量向量（MMV），通过多任务贝叶斯压缩感知（MT-BCS）算法对各个极化通道的测量数据进行联合处理从而实现各个极化通道对应的探测场景反射率的重建。基于时域有限差分（FDTD）法的仿真数据处理结果表明所提成像算法在目标位置重建的准确性和背景杂波抑制能力上均优于单测量向量（SMV）模型的极化探地雷达成像算法。     

给你的相机找问题 如何分辨噪点缺陷

什么是噪点噪点数码相机的噪点(noise)也称为噪声、噪音,主要是指CCD(CMOS)将光线作为接收信号接收并输出的过程中所产生的图像中的粗糙部分,也指图像中不该出现的外来像素,通常由电子干扰产生。看起来就像图像被弄脏了,布满一些细小的糙点。我们平时所拍摄的数码照片如果用个人电脑将拍摄到的高画质图像缩小以后再看的话,也许就注意不到。不过,如果将原图像放大,那么就会出现本来没有的颜色(假色),这种假色就是图像噪音。除了噪点外,还有一种现像很容易与噪点相混淆,这就是坏点。在数码相机同一设置条件下,如果所拍的图像中杂点总是出现在同一个位置,就说明这台数码相机存在坏点,一般厂家对坏点的数量有规定,如果坏点数量超过了规定的数量,可以向经销商和厂家更换相机。假如杂点并不是出现     

基于Pauli基展开的联合极化SAR微多普勒分析

为获取不同极化通道的微多普勒元素,建立了双通道极化合成孔径雷达微动信号获取模型,详细推导了采用相位中心偏置天线(DPCA)技术剔除地杂波后的极化微多普勒参数化表述。在此基础上,为充分融合各极化通道信息,提出了一种基于Pauli基展开的联合极化微多普勒矢量提取方法,据此可显著增强低信噪比下的微多普勒特征。仿真数据验证了该方法的有效性。     

Bayesian multi-resolution spatial analysis with applications to marketing

Marketing researchers have become increasingly interested in spatial datasets. A main challenge of analyzing spatial data is that researchers must a priori choose the size and make-up of the areal units, hence the resolution of the analysis. Analyzing the data at a resolution that is too high may mask ??macro?? patterns, while analyzing the data at a resolution that is too low may result in aggregation bias. Thus, ideally marketing researchers would want a ??data-driven?? method to determine the ??optimal?? resolution of analysis, and at the same time automatically explore the same dataset under different resolutions, to obtain a full set of empirical insights to help with managerial decision making. In this paper, we propose a new approach for multi-resolution spatial analysis that is based on Bayesian model selection. We demonstrate our method using two recent marketing datasets from published studies: (i) the Netgrocer spatial sales data in Bell and Song (Quantitative Marketing and Economics 5:361?C400, 2007), and (ii) the Pathtracker^? data in Hui et al. (Marketing Science 28:566?C572, 2009b; Journal of Consumer Research 36:478?C493, 2009c) that track shoppers?? in-store movements. In both cases, our method allows researchers to not only automatically select the resolution of the analysis, but also analyze the data under different resolutions to understand the variation in insights and robustness to the level of aggregation.     

Nationality biases in peer evaluations: The country-of-origin effect in global virtual teams

In a post-COVID-19 world, due to the increasing reliance on virtual work, global virtual teams (GVTs) are critical for the international success of firms. A fundamental challenge that firms face in this new remote work context is the need to measure the performance of individuals in GVTs. Peer evaluations are advocated as a way to improve the validity of performance appraisals. Peers work closely with one another and, presumably, are better positioned to observe and evaluate fellow team members’ performance. Even when completed in good faith, however, a fair evaluation of individual contributions and performance in GVTs could be distorted by subjectivity, bias, cultural and institutional differences, and the limitations of online communication tools. Based on a sample of 6634 GVTs comprised of 33,271 people in 79 countries that worked on an international business (IB) project, we tested the country-of-origin (COO) effect in peer evaluations within the context of GVTs. Results indicate that the nationality of the team member is a source of significant bias in peer evaluations. Our tests show that the prestige and the level of economic development of the country that a team member is from is a better predictor of peer evaluations received than objective measures of individual skills and competencies, including English proficiency, technical ability, and cultural intelligence, or national per-capita spending on education, suggesting that a COO effect based on personal bias may affect performance ratings more than actual contributions. We conclude that the COO effect in peer evaluations in GVTs has to be taken into account when designing evaluation systems and discuss implications for theory, practice and future research.     

Competitive reaction- and feedback effects based on VARX models of pooled store data

We apply a model that accommodates dynamic phenomena in demand- and reaction functions. The latter functions capture reactions to actions as well as to consequences of actions. We estimate a fixed effects VARX model with dynamic and interactive effects for multiple brands based on pooled time series and cross-sectional data for two product categories. The Impulse Response Analysis (IRA) results for one category (tuna) under different scenarios show that the inclusion/exclusion of competitive reaction- and feedback effects matters a lot, consistent with a high degree of competitive interaction in this market. We find that the role of cross-brand feedback effects is greater than the role of traditional competitive reaction effects. Intrafirm effects (internal decisions) also play an important role. In a decomposition study we show that the exclusion of these effects may either increase (up to 12%) or decrease (by as much as 50%) the net unit sales effect of a 20% price reduction. By contrast, in the second category (shampoo), where brands have distinct positions, the exclusion of these effects matters very little.     

融合改进FT显著性与Grabcut的图像目标分割算法

针对目前复杂度较大的图像中目标分割速度较慢、显著性边界分割不明确等问题,提出了一种融合改进的FT（Frequency-tuned）显著性检测与Grabcut的图像分割算法。该算法首先通过改进基于频率调谐的FT显著性检测方法得到图像中显著性较高的区域,并利用SLIC（Simple Linear Iterative Clustering）算法对显著图进行预处理得到超像素图,能够有效改善边界的分割效果,然后通过以图论GraphCut算法为基础改进的Grabcut算法建立高斯混合模型。为了提高算法效率,通过聚类以超像素代替原像素,并反复迭代高斯混合模型（Gaussian Mixed Model,GMM）参数,最后利用最大流最小割算法得到最优目标分割结果。实验结果表明所提算法能够更准确更高效率地分割图像中的显著性目标,对高分辨率图像也有很好的适用效果,相比于其他算法在分割精度上提高10%左右,并具有较高的分割效率。     

Road safety mass media campaigns: Why are results inconclusive,and what can be done?

Recent research literature on the effectiveness (or otherwise) of promoting road safety via mass media advertising is selectively reviewed. The overall picture from this is inconclusive: effects of substantial size have been rare, but effects of small size cannot be ruled out. It is then argued that attempts to use crash data to establish or disprove the cost-effectiveness of campaigns are, indeed, doomed to failure: the random variability in crash numbers is too great (and even low effectiveness may be sufficient as campaigns are very cheap per person reached). It is suggested that evaluation may need to be based on before and after comparison of behaviours or variables that can be objectively observed and are closely linked to safety – and in order to substantiate the behaviour-safety link, credible theories are needed.     

Road safety mass media campaigns: why are results inconclusive, and what can be done?

Recent research literature on the effectiveness (or otherwise) of promoting road safety via mass media advertising is selectively reviewed. The overall picture from this is inconclusive: effects of substantial size have been rare, but effects of small size cannot be ruled out. It is then argued that attempts to use crash data to establish or disprove the cost-effectiveness of campaigns are, indeed, doomed to failure: the random variability in crash numbers is too great (and even low effectiveness may be sufficient as campaigns are very cheap per person reached). It is suggested that evaluation may need to be based on before and after comparison of behaviours or variables that can be objectively observed and are closely linked to safety - and in order to substantiate the behaviour-safety link, credible theories are needed.     

利用参考波形估计导航信号测距偏差

针对卫星导航信号存在的微小信号畸变,研究了因导航信号畸变而引起的测距偏差的估计问题。基于理想矩形脉冲波形和真实信号波形的上升沿零交叉点信息,给出参考波形定义,并以此为基础估计测距偏差。该方法可用于定量评估卫星导航信号波形畸变对测距偏差的影响及比较卫星之间的测距差异。以二阶模型为基础产生畸变波形,验证了该方法的有效性,并分析了估计精度与信噪比关系。通过大口径天线采集“北斗”卫星B1频点信号,利用该方法获得了B1频点I/Q支路信号的测距偏差,表明该方法可用于在轨卫星信号的测距性能评估。