Rendering 2D Lines on 3D Terrain Model with Optimization in Visual Quality and Running Performance

With the gradual shift from 2D maps to a 3D virtual environment, various visual artifacts were generated by overlaying 2D map symbols on 3D terrain models. This work proposes a novel screen‐based method for rendering 2D vector lines with the accuracy of more than one pixel on the screen in real time. First, screen pixels are inversely projected onto a 3D terrain surface, and then onto the 2D vector plane. Next, these pixels are classified into three categories in terms of their intersection situation with the 2D lines. After that, a multiple sampling process is applied to the pixels that intersect with the 2D lines in order to eliminate visual artifacts, such as intermittence and aliasing (in pixel scale). Finally, a suitable point‐in‐polygon judgment is implemented to color each sample point quickly. The algorithm is realized in a heterogeneously parallel model so that the performance is improved and becomes acceptable.     

地图目标局部分形描述的元分维模型的实现

提出了一种基于分形理论的元分维模型，可以用于描述地图目标的局部形态特征变化，为地图目标的进一步分析应用提供了一个新的思路。     

Cartographic reconstruction of building footprints from historical maps: A study on the Swiss Siegfried map

Extracting features from printed maps has been a challenge for decades; historical maps pose an even larger problem due to manual, inconsistent drawing or scribing, low printing quality, and geometrical distortions. In this article, a new workflow is introduced, consisting of a segmentation step and a vectorization step to acquire high‐quality polygon representations of building footprints from the Siegfried map series. For segmentation, an ensemble of U‐Nets is trained, yielding pixel‐based predictions with an average intersection over union of 88.2% and an average precision of 98.55%. For vectorization, methods based on contour tracing and orientation‐based clustering are proposed to approximate idealized polygonal representations. The workflow has been tested on 10 randomly selected map sheets from the Siegfried map, showing that the time required to manually correct these polygons drops to about 45 min per map sheet. Of this sample, approximately 10% of buildings required manual corrections. This workflow can serve as a blueprint for similar vectorization efforts.     

SAR影像与光学影像的高斯伽玛型边缘强度特征匹配法

提出了一种基于影像边缘强度图描述的SAR影像与光学影像匹配方法。首先对影像进行粗纠正,消除影像之间的尺度和旋转变化;其次,改进相位一致性特征检测方法,提取对影像相干斑噪声稳健的特征点;然后基于高斯伽玛型双边窗口比值算子计算影像边缘强度图,在此基础上构造不变特征描述符;最后联合几何约束条件,实现SAR影像与光学影像匹配。试验结果证明,与现有方法相比,本文方法能够大幅提高SAR影像与光学影像匹配结果中的正确匹配特征数量以及影像配准精度。     

Data matching of building polygons at multiple map scales improved by contextual information and relaxation

The aim of matching spatial data at different map scales is to find corresponding objects at different levels of detail (LODs) that represent the same real-world phenomena. This is a prerequisite for integrating, evaluating and updating spatial data collected and maintained at various scales. However, matching spatial data is not straightforward due to the ambiguities caused by problems like many-to-many correspondence, non-systematic displacement and different LODs between data sets. This paper proposes an approach to matching areal objects (e.g. buildings) based on relaxation labeling techniques widely applied in pattern recognition and computer vision. The underlying idea is to utilize contextual information (quantified by compatibility coefficient) in an iterative process, where the ambiguities are reduced until a consistent matching is achieved. This paper describes (1) a domain-specific extension to previous relaxation schemes and (2) a new compatibility coefficient that exploits relative relationships between areal object pairs in spatial data. Our approach were validated through extensive experiments using building data sets at 1:10k and 1:50k as an example. Our contextual approach showed superior performance against a non-contextual approach in general and especially in ambiguous situations. The proposed approach can also be applied to matching other areal features and/or for a different scale range.     

基于边缘提取和改进型整体松弛匹配算法的InSAR复图像配准方法

配准精度是InSAR合成孔径雷达干涉成像技术中的重要指标。为获得高精确度的测量结果,提出一种包括概略配准、像素级初配准和亚像素级精配准三个环节的逐级提高精度的InSAR复图像配准方法。利用EnView软件提供的经度和纬度实现概略配准、采用基于多边形结构和边缘提取的像素级初匹配方法大大提高匹配速度。考虑以往的匹配算法都是基于能量图进行并且忽略了整体性,采用基于整体松弛匹配和相位最小二乘匹配相结合的亚像素级精匹配算法减少误匹配率,提高匹配精度。实验结果证明该方法具有良好的性能。     

基于三角网的"种子法"多边形生成

将传统上广泛使用的“种子法”和“矢量求交法”的思想相结合 ,提出了一种基于约束Delaunay三角网结构的多边形生成算法。详细描述了该方法的基本思想 ,在实验基础上分析了算法的特点。     

同名边界点的面状居民地要素匹配

针对空间数据集成与地图增量更新过程中的面实体匹配环节,该文提出利用同名边界点集进行面状居民地要素匹配的方法。该方法从边界点的相似性考虑面状居民地要素的相似性,通过计算候选匹配要素上边界点在位置、转角、关联边等方面的一致性,把面实体相似性的比较转换为同名要素边界点集相似性的比较,简化了面状居民地实体匹配的复杂度。在面状居民地要素的匹配过程中,该文方法可以处理一对一、一对多和多对一的匹配关系。实验证明,该方法在匹配面状居民地要素时,准确率可以达到98%。     

What is the difference between two maps? A remote senser’s view

In remote sensing, thematic map comparison is often undertaken on a per-pixel basis and based upon measures of classification agreement. Here, the degree of agreement between two thematic maps, and so the difference between the pair, was evaluated through visual and quantitative analyses for two scenarios. Quantitative assessments were based on basic site-specific measures of agreement that are used widely in accuracy assessment (e.g. the overall percentage of pixels with the same class label in each of the two maps and the kappa coefficient of agreement) as well as an information theory based approach that allows the degree of mutual or shared information to be assessed even if different classification schemes have been used to produce the maps. The results indicated that in the first map comparison scenario, focused on labelling, there was a fair degree of correspondence between the maps but with an overall difference in information content of ∼42%. In the second comparison scenario, focused on change in time, considerable change had occurred with a change in class label for ∼42% of the pixels. It was also apparent that global assessments masked local scale changes.     

基于Monte Carlo方法的不确定性地理现象可视化

应用Monte Carlo方法伪随机数模拟表达随机过程现象的数学方法，并结合粒子系统模型提出了一种地理现象空间分布不确定性特征的动画可视化方法。通过栅格单元的随机运动，从视觉上表达现象分布在空间定位、属性特征上的不确定性、模糊性，同时由Monte Carlo方法控制随机过程中现象分布的统计规律。     

多尺度面实体的匹配方法研究

从多尺度面实体匹配的需要出发,分析地图综合所引起的一对多、多对多匹配关系,以及不同地图综合算子给同名实体所造成的差异,将一对一匹配关系的几何相似性度量模型和非一对一匹配关系的基于重叠度的面实体匹配方法相结合,采用指标阈值自动确定方法,建立一种新的适用多尺度变化的面实体匹配方法。最后以多个比例尺的居民地为实验对象,验证本方法的可行性和有效性。     

SAR立体影像匹配的视差图融合方法

提出了一种基于视差图融合的匹配方法。首先,基于归一化互相关系数(normalized cross correlation,NCC),利用多个不同尺寸的匹配窗口分别进行匹配,获取相应的视差图;然后,提出了一种左右一致性(left right consistency,LRC)和信噪比(signal to noise ratio,SNR)相结合的置信测度,用来评价视差图中每个视差的置信水平;在此基础上,提出了一种视差图融合策略,该策略对上述多个匹配窗口获取的视差图进行加权融合,融合时既考虑了视差本身的置信水平,也兼顾了其邻域视差的影响。采用TanDEM-X的聚束立体影像进行试验,结果表明,本文方法能有效减少DEM粗差点,DEM高程精度由11.28 m提高到8.41 m。     

一种应用三角形划分的空间对象形状匹配方法

为解决现有空间对象形状相似性匹配准确率较低的问题,提出一种应用三角形划分的形状相似性匹配方法。该方法按形状主方向对面状空间对象进行分割,按串联、并联和组合形式对空间对象进行三角形划分,准确描述面状空间对象的形状特征,度量空间对象间的形状相似性。通过形状数据集匹配、不同年份面状水系图层匹配和矢量地图草图检索,测试本方法的形状检索性能,并和其他空间对象形状匹配方法进行对比。实验结果表明,本方法具有更高的形状检索准确率。三角形划分形状匹配方法具有平移、旋转、尺度不变性和较强的形状描述识别能力。     

Knowledge Discovery from Area–Class Resource Maps: Capturing Prototype Effects

This paper presents a knowledge discovery approach to extracting knowledge from area–class resource maps. Prototype theory forms the basis of the approach which consists of two major components: (1) a scheme for organizing knowledge used in categorizing geographic entities which allows for the modeling of indeterminate boundaries and non–uniform memberships within categories; and (2) a data mining method using the Expectation Maximization (EM) algorithm for extracting such knowledge from area–class maps. A case study on knowledge discovery from a soil map demonstrates the details of the approach. The study shows that knowledge for classifying geographic entities with indeterminate boundaries is embedded in area–class maps and can be extracted through data mining; and that continuous spatial variation of geographic entities can be better modeled if the knowledge discovery process retains knowledge of within-class variations as well as transitions between classes.     

基于穷举法的高光谱遥感图像地物识别研究

介绍了一种基于穷举法的高光谱遥感图像地物识别方法.该方法从所有与研究区有关的可能参考光谱中识别出图像上每个像元的最佳匹配光谱,绘制识别结果图,并由图中信息可对参考光谱进行更换,以求得最佳识别结果.并以云南省中甸普朗斑岩铜矿区外围的高光谱遥感图像为例,得到了该区的地物识别图,经实地检验,证实了该方法的有效性.     

基于交互式分割技术和决策级融合的SAR图像变化检测

为免去去除斑点噪声的预处理操作及克服选择分布模型的限制,本文结合差异图的特点和一种不涉及分布模型的交互式分割方法,产生不同“种子点”下的变化检测结果后,再利用投票策略对其进行决策级的融合给出最终的变化检测结果。分割中,将每个像素的特征设为差异图及由静态小波变换分解差异图再丢弃高频系数后重构得到的各层表示中,其对应位置上的灰度值构成的矢量。此特征及决策级融合的策略使本文的变化检测技术对SAR图像中的斑点噪声具有一定的鲁棒性。在无需对SAR图像做预处理的情况下,对真实SAR图像数据集的变化检测结果,其效果优于其他相关技术的。     

拓扑多边形自相交判断及纠正方法

提出了一种解决地形图处理中拓扑多边形自相交问题的方法。首先在原多边形内部构建新多边形,通过判定新多边形的顶点是否为原多边形内点实现了多边形自相交的判断。最后利用三种方式对存在自相交的多边形进行纠正。基于VC＋＋6.0实现相关功能,并以实例验证了这一方法的稳定性和可行性。     

Line segment confidence region-based string matching method for map conflation

In this paper, a method to detect corresponding point pairs between polygon object pairs with a string matching method based on a confidence region model of a line segment is proposed. The optimal point edit sequence to convert the contour of a target object into that of a reference object was found by the string matching method which minimizes its total error cost, and the corresponding point pairs were derived from the edit sequence. Because a significant amount of apparent positional discrepancies between corresponding objects are caused by spatial uncertainty and their confidence region models of line segments are therefore used in the above matching process, the proposed method obtained a high F-measure for finding matching pairs. We applied this method for built-up area polygon objects in a cadastral map and a topographical map. Regardless of their different mapping and representation rules and spatial uncertainties, the proposed method with a confidence level at 0.95 showed a matching result with an F-measure of 0.894.     

运用图论进行道路网网格模式提取

提出了一种基于图论的网格模式提取方法。该方法根据道路之间的关系生成关系图,运用交、联、提取连通分量和极大完全子图等图论算子完成模式的提取。实验结果表明,该方法能有效地进行网格模式的提取。