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联合实、复相关函数的干涉SAR图像配准方法 总被引:1,自引:1,他引:0
SAR复图像配准是干涉SAR数据处理中的关键步骤之一,配准精度直接影响后续产品的质量。提出一种基于联合实、复相关函数的星载干涉SAR图像配准方法。首先,在分析已有配准测度函数各自特性的基础上,结合国际上干涉SAR数据处理经验,认为在全球干涉测量任务背景下,相关函数是一种稳健、普适性的干涉SAR图像配准测度函数。然后,针对相关函数存在实、复相关计算,分析实、复相关函数各自的特点以及适应情况,提出配准灵敏度准则,从而能够有效地自适应地选取相应的配准相关度量。最后,给出配准算法的详细实现步骤。复杂地区的实测数据处理结果验证了方法的有效性。 相似文献
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分析了传统点位不确定性指标的局限性,基于信息论中的联合熵和最大熵定理导出了n维随机点熵不确定指标以及落入其内概率的统一公式;提出了以熵误差椭圆与熵误差椭球作为2维、3维GIS中点元的位置不确定性度量指标.提出的熵指标具有唯一确定、不受置信水平选取的主观性影响等特点,适合于度量未知分布的点位不确定性. 相似文献
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熵理论在确定点位不确定性指标上的应用 总被引:3,自引:0,他引:3
分析了传统点位不确定性指标的局限性,基于信息论中的联合熵和最大熵定理导出了n维随机点熵不确定指标以及落入其内概率的统一公式;提出了以熵误差椭圆与熵误差椭球作为2维、3维GIS中点元的位置不确定性度量指标。提出的熵指标具有唯一确定、不受置信水平选取的主观性影响等特点,适合于度量未知分布的点位不确定性。 相似文献
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《地理空间信息》2020,(6)
针对传统ICP配准算法无法抵抗常规粗差点对配准精度的影响问题,研究了基于配准残差分布函数点对定权的改进ICP配准算法,推导了基于配准残差分布函数的点对残差权重值计算公式,在此基础上采用幂法解算单位四元数,最终在速度和精度2个方面完成对原始ICP配准算法的优化。采用C~(++)编程语言将改进的ICP点云配准算法程序化,利用Rigel LMS-Z420i三维激光扫描仪对某雕像进行扫描,通过自编程序对含有常规粗差点的点云数据进行配准实验,将基于点对权重的改进ICP算法与标准ICP算法进行比较,结果表明基于点对权重的改进ICP算法能够有效处理配准数据中存在粗差点的情况,是一种比较精确的抗差配准算法,可对现存配准算法进行有效补充。 相似文献
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提出了一种基于核函数度量相似性的遥感影像变化检测算法。该算法通过比较两个时相特征向量的概率密度进行变化判别,将概率密度的比较转化成核函数的形式,利用核函数的相似度量功能进行变化判别,通过指定的核函数避开概率密度的估计,达到概率密度比较的目的。 相似文献
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变形监测中GPS信号衍射误差的环境建模法,论空间数据处理与空间数据挖掘,基于线扩散函数的高精度轮廓特征提取算法,基于WebService的小流域地貌演化问题计算设计与实现,坐标参数为长度量的一种新型的大地坐标系,基于特征的面向对象虚拟G1S数据模型 相似文献
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尺度不变特征转换(scale invariant feature transform,SIFT)是一种广泛应用于图像配准领域的点特征提取算法。针对基于SIFT的图像自动配准算法存在的特征点分布不均匀问题,提出了一种基于势函数点分布调整的图像配准方法。该方法解决了SIFT算法不能针对特征点的分布情况进行优化的问题。通过调整SIFT的比值阈值,增加配准点的数目;通过引入分子力学中的势函数概念,对特征点分布情况进行优化;通过局部互信息精纠正,微调特征点位置,以提高特征配准点的配准精度;最终实现高质量(空间分布均衡,配准精度高)的图像自动配准。 相似文献
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面域拓扑图是一种利用区域面积大小定量表达区域属性信息的可视化方法。由于其区域面积本身已经表示某一变量,因此这更有利于双/多变量的制图表达。针对目前基于面域拓扑图的双/多变量表达方法中存在的难以表达相邻区域之间基本状况和不利于不同地理现象的空间分布规律及差异表达的问题,本文提出一种面向双/多变量的连续面域拓扑图可视化方法。首先通过格网密度补偿和积分步长逐步试探的方法对基于扩散模型的连续面域拓扑图生成算法进行部分优化,完成基本变量的表达,然后分别通过空间内插和符号扩展完成第2和第3变量在连续面域拓扑图中的表达。最后以慕尼黑市人口密度和银行/ATM分布(双变量)数据以及奥格斯堡市人口密度数据、幼儿园分布以及规模数据(多变量)为试验数据进行可视化,并通过实证分析验证了该方法的有效性和优越性。 相似文献
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L. Mathys A. Guisan T.W. Kellenberger N.E. Zimmermann 《ISPRS Journal of Photogrammetry and Remote Sensing》2009,64(6):665-673
Continuous field mapping has to address two conflicting remote sensing requirements when collecting training data. On one hand, continuous field mapping trains fractional land cover and thus favours mixed training pixels. On the other hand, the spectral signature has to be preferably distinct and thus favours pure training pixels. The aim of this study was to evaluate the sensitivity of training data distribution along fractional and spectral gradients on the resulting mapping performance.We derived four continuous fields (tree, shrubherb, bare, water) from aerial photographs as response variables and processed corresponding spectral signatures from multitemporal Landsat 5 TM data as explanatory variables. Subsequent controlled experiments along fractional cover gradients were then based on generalised linear models.Resulting fractional and spectral distribution differed between single continuous fields, but could be satisfactorily trained and mapped. Pixels with fractional or without respective cover were much more critical than pure full cover pixels. Error distribution of continuous field models was non-uniform with respect to horizontal and vertical spatial distribution of target fields. We conclude that a sampling for continuous field training data should be based on extent and densities in the fractional and spectral, rather than the real spatial space. Consequently, adequate training plots are most probably not systematically distributed in the real spatial space, but cover the gradient and covariate structure of the fractional and spectral space well. 相似文献
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InSAR相位解缠算法比较及误差分析 总被引:6,自引:0,他引:6
介绍和比较了残差缺口法、最小二乘法和统计耗费网络流算法 ,并研究了解缠相位误差对DEM和地壳变形的影响。通过理论分析和实际计算发现 ,无论计算效率还是解缠精度 ,残差缺口法都优于最小二乘法。统计耗费网络流算法在残差缺口算法基础上又有创新 ,是一种最具潜力的新型算法 相似文献
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There are various occasions where simple, ordinary, and universal kriging techniques may find themselves incapa- ble of performing spatial prediction directly or efficiently. One type of application concerns quantification of cumulative distribution function (CDF) or probability of occurrences of categorical variables over space. The other is related to optimal use of co-variation inherent to multiple regionalized variables as well as spatial correlation in spatial prediction. This paper extends geostatistics from the realm of kriging with uni-variate and continuous regionalized variables to the territory of indicator and multivariate kriging, where it is of ultimate importance to perform non-parametric estimation of probability distributions and spatial prediction based on co-regionalization and multiple data sources, respectively. 相似文献
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Proximity-based grouping of buildings in urban blocks: a comparison of four algorithms 总被引:4,自引:0,他引:4
Grouping of buildings based on proximity is a pre-processing step of urban pattern (structure) recognition for contextual cartographic generalization. This paper presents a comparison of grouping algorithms for polygonal buildings in urban blocks. Four clustering algorithms, Minimum Spanning Tree (MST), Density-Based Spatial Clustering Application with Noise (DBSCAN), CHAMELEON and Adaptive Spatial Clustering based on Delaunay Triangulation (ASCDT) are reviewed and analysed to detect building groups. The success of the algorithms is evaluated based on group distribution characteristics (i.e. distribution of the buildings in groups) with two methods: S_Dbw and newly proposed Cluster Assessment Circles. A proximity matrix of the nearest distances between the building polygons, and Delaunay triangulation of building vertices are created as an input for the algorithms. A topographic data-set at 1:25,000 scale is used for the experiments. Urban block polygons are created to constrain the clustering processes from topological aspect. Findings of the experiment demonstrate that DBSCAN and ASCDT are superior to CHAMELEON and MST. Among them, MST has exhibited the worst performance for finding meaningful building groups in urban blocks. 相似文献