基于Harris和SURF的遥感图像匹配方法研究

针对多源遥感图像匹配正确率低的问题,本文首先采用点空间约束的Harris角点检测算法,得到分布比较均匀的角点;接着构建Voronoi图进行图像分块;然后应用分块SURF特征点检测和匹配得到仿射变换参数;再利用灰度积相关算法实现同名点搜索;最后辅以两点对空间约束剔除误匹配。实验结果表明,本文采用的基于Harris和SURF的方法在遥感图像匹配正确率和效率上优于SURF算法。     

倾斜影像的量测方法研究

随着“数字地球”“数字城市”的提出,能够快速获取空间数据基础信息成为当今急需解决的问题之一。传统的航空摄影测量主要是对地物顶部信息的获取,而对侧面信息获取比较困难,因此倾斜航空测量技术成为国内外快速发展起来的一门高新技术。本文主要论述了基于倾斜影像量测的几种方法,并对以后量测方法的发展趋势进行了说明。     

基于像方特征点的多视影像最小二乘匹配

为了能得到更精确的影像初始值,进行高精度的影像匹配,本文分别选取了两种物方多视匹配模型和不同匹配策略、不同约束条件下的影像粗匹配结果作为初始值进行最小二乘精匹配。实验结果表明物方匹配模型可以提供很精确的初始值,而金字塔、视差和共线方程共同约束下的最小二乘匹配精度更高,可靠性、鲁棒性及稳定性更好,验证了结合合理的匹配策略和约束方法的最小二乘优化可以将匹配精度达到1／10000精度。     

浅谈VirtuoZo和MapMatrix在3D产品中的应用

主要论述了数字摄影测量系统MapMatrix和VirtuoZo的一些异同点。     

Enrichment of topographic road database for the purpose of routing and navigation

With growing demand on multi-purpose or multi-modal navigation, the route calculation needs to traverse semantically enriched road networks for different transportation modes. Currently, operational route planning algorithms reveal rather limited performances or their potential for comprehensive applications are constrained by the unavailable or insufficient interoperation among the underlying geo-data that are separately maintained in different spatial databases. To overcome this limitation, a novel approach has been proposed to integrate the routing-relevant information from different data sources, which involves three processes: (1) automatic matching to identify the corresponding road objects between different datasets; (2) interaction to refine the automatic matching result; and (3) transferring the routing-relevant information from one data-set to another. In process (1), the Delimited Stroke Oriented algorithm is employed to achieve the automatic data matching between different datasets, which has revealed a high matching rate and certainty. However uncertain matching problems occur in areas where topological conditions are too complicated or inconsistent. The remaining unmatched or wrongly matched objects are treated in process (2), with the help of a series of interaction tools. On the basis of refined matching results after the interaction, process (3) is dedicated to automatic integration of the routing-relevant information from different data sources.     

Tracking of facial deformations in multi-image sequences with elimination of rigid motion of the head

The paper deals with measurement of human facial deformations from synchronized image sequences taken with multiple calibrated cameras from different viewpoints. SIFT (Scale Invariant Feature Transform) keypoints are utilized as image feature points in the first place to determine spatial and temporal correspondences between images. If no temporal match is found for an image point by keypoint matching, then the tracking of the point is switched to least squares matching provided the point has one or more spatial corresponding points in the other views of the previous frame. For this purpose, a new method based on affine multi-image least squares matching is proposed where multiple spatial and temporal template images are simultaneously matched against each search image and part of the spatial template images also change during adjustment. A new method based on analyzing temporal changes in the image coordinates of the tracked points in multiple views is then presented for detecting the 3-D points which move only rigidly between consecutive frames. These points are used to eliminate the effect of rigid motion of the head and to obtain the changes in the 3-D points and in the corresponding image points due to pure deformation of the face. The methods are thoroughly tested with three multi-image sequences of four cameras including also quite large changes of facial deformations. The test results prove that the proposed affine multi-image least squares matching yields better results than another method using only fixed templates of the previous frame. The elimination of the effect of rigid motion works well and the points where the face is deforming can be correctly detected and the true deformation estimated. A method based on a novel adaptive threshold is also proposed for automated extraction and tracking of circular targets on a moving calibration object.     

利用外部DEM辅助山区SAR立体像对匹配及地形制图

SAR立体像对的匹配是利用雷达摄影测量技术提取地形高程信息的关键,匹配精度将直接影响结果 DEM的高程精度。针对山区SAR立体像对匹配过程中同名点选取困难的问题,引入外部粗分辨率DEM作为辅助数据,将该DEM高程转换为视差,为匹配提供初值,同时采用金字塔匹配策略,不仅可以缩小搜索范围,提高搜索效率,而且能够减少粗差的产生。试验结果表明,采用外部DEM辅助之后,匹配粗差点数量相对于传统的雷达摄影测量处理结果明显减少,从而有效地提高了高程信息提取重建的精度。     

地磁匹配中的地磁日变效应

针对目前地磁匹配研究中往往忽略地磁日变的影响,文中分别基于IGRF11模型和MAD匹配算法探讨了地磁匹配中的地磁日变效应.基于IGRF11模型的定性分析表明,地磁日变效应显著,即使在地磁变化较为平缓的区域,地磁日变仍给匹配定位带来较大影响.分别利用地磁平静时期广州、兰州、北京十三陵3个地磁台站分均值数据,基于MAD匹配算法定量分析了地磁日变效应.结果表明,匹配定位误差呈现出类似于日变形态的变化特征,且纬度效应显著,广州台站纬度方向上的最大误差达0.189°,经度误差达0.492°.     

3维最小二乘表面匹配泛型数学模型及在机载LiDAR条带平差中的应用

以3维表面间共轭点欧氏距离之和最小为理论基础,提出一种泛型3维表面匹配数学模型,并推导其最小二乘平差理论模型,利用该模型进行机载LiDAR点云条带平差。针对真实机载LiDAR点云数据进行条带平差对比实验,结果表明本文所提出的表面匹配模型,不仅能准确估计出相邻重叠3维表面间的正形变换参数,较好地解决机载LiDAR点云条带间配准问题,而且能同时适用于多种同名点对应准则,是一种泛型的配准模型。     

Automatic change detection for road networks from images based on GIS

Up to now, detailed strategies and algorithms of automatic change detection for road networks based on GIS have not been discussed. This paper discusses two different strategies of automatic change detection for images with low resolution and high resolution using old GIS data, and presents a buffer detection and tracing algorithm for detecting road from low-resolution images and a new profile tracing algorithm for detecting road from high-resolution images. For feature-level change detection (FL-CD), a so-called buffer detection algorithm is proposed to detect changes of features. Some ideas and algorithms of using GIS prior information and some context information such as substructures of road in high-resolution images to assist road detection and extraction are described in detail.