共查询到20条相似文献，搜索用时 86 毫秒
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Automatic change detection and geo-database updating in the urban environment are difficult tasks. There has been much research on detecting changes with satellite and aerial images, but studies have rarely been performed at the street level, which is complex in its 3D geometry. Contemporary geo-databases include 3D street-level objects, which demand frequent data updating. Terrestrial images provides rich texture information for change detection, but the change detection with terrestrial images from different epochs sometimes faces problems with illumination changes, perspective distortions and unreliable 3D geometry caused by the lack of performance of automatic image matchers, while mobile laser scanning (MLS) data acquired from different epochs provides accurate 3D geometry for change detection, but is very expensive for periodical acquisition. This paper proposes a new method for change detection at street level by using combination of MLS point clouds and terrestrial images: the accurate but expensive MLS data acquired from an early epoch serves as the reference, and terrestrial images or photogrammetric images captured from an image-based mobile mapping system (MMS) at a later epoch are used to detect the geometrical changes between different epochs. The method will automatically mark the possible changes in each view, which provides a cost-efficient method for frequent data updating. The methodology is divided into several steps. In the first step, the point clouds are recorded by the MLS system and processed, with data cleaned and classified by semi-automatic means. In the second step, terrestrial images or mobile mapping images at a later epoch are taken and registered to the point cloud, and then point clouds are projected on each image by a weighted window based z-buffering method for view dependent 2D triangulation. In the next step, stereo pairs of the terrestrial images are rectified and re-projected between each other to check the geometrical consistency between point clouds and stereo images. Finally, an over-segmentation based graph cut optimization is carried out, taking into account the color, depth and class information to compute the changed area in the image space. The proposed method is invariant to light changes, robust to small co-registration errors between images and point clouds, and can be applied straightforwardly to 3D polyhedral models. This method can be used for 3D street data updating, city infrastructure management and damage monitoring in complex urban scenes. 相似文献
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Zhizhong Kang Liqiang Zhang Sisi Zlatanova Jonathan Li 《ISPRS Journal of Photogrammetry and Remote Sensing》2010,65(3):282-293
This paper presents an automatic mosaicking method for generating building facade textures from a monocular close-range digital image sequence. The process begins with the computation of the camera parameters (except the coordinates of the projective center), which are determined by combining vanishing point geometry with constraints of a straight line bundle as well as prior information of parallel lines in object space. The raw images are later rectified for the purpose of eliminating their salient geometric distortion. Next, automatic retrieval of the relevant image segment is implemented using the detecting range variance by means of the histogram of projective differences between the corresponding points for each of the facades from the raw image sequence. A strip model of the least-squares adjustment, which is similar to the strip block adjustment in aerial triangulation, is employed to determine the spatial alignment of each of the image segments in order to generate the facade textures from the relevant image segments. Afterwards, the entire building facade texture is mosaicked by ortho-image generation. Two refining strategies are proposed to optimize the mosaic result. One is refining the mosaic region where corresponding points are difficult to match but plenty of horizontal lines are available, and the constraint of corresponding horizontal lines is introduced to implement this process. The other strategy is to refine the unsatisfactory mosaic region by densifying the corresponding points by means of the spatial alignment of the relevant image segment computed by the strip method. The experimental results indicate that this method is widely applicable and compares well with other reported approaches with regard to automation level and applicability, for uncalibrated images as well as images with large geometric distortions. 相似文献
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车道线检测是自动驾驶汽车或高级驾驶辅助系统的重要组成部分，利用安装在车辆前方的单目相机以实时成像的方式获取车辆在当前车道的横向偏移，从而为车辆的车道保持、超车换道等横向控制策略提供参考。本文提出了一种基于双灭点估计的实时、稳健的车道检测方法。首先利用尺度自适应的局部对称算子对车道线点特征进行提取；其次对左右车道线分别估计灭点，以灭点为导向，构建特征点的统计直方图；然后选择穿过大多数特征点的直线且通过特征点和所选线之间的重叠度对灭点进行估计更新，重复上一步骤以获得稳定的灭点；最后基于稳定的灭点验证并选择最佳的车道线。本文在公共数据集对提出的方法进行了测试，试验结果表明，本文方法在满足实时性的前提下，能有效提高算法整体的稳健性。 相似文献
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提出了一种基于亮度空间和相位一致性理论的多光谱遥感影像特征点检测算法。首先利用参数自适应的灰度变换函数建立影像亮度空间;然后结合相位一致性方法在影像亮度空间进行候选特征点检测,并将候选特征点映射到原始影像上进行非极大值抑制;最后在尺度空间计算特征点的特征尺度值。本文方法有效结合了亮度空间特征检测和相位一致性特征检测的优势,对多光谱遥感影像的辐射变化具有较强的稳健性。试验结果证明,与传统特征点检测算法相比,本文方法在特征重复率和重复特征数量方面都具有明显的优势。 相似文献
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建筑物提取一直是机载激光点云数据处理研究的热点,其中建筑物和其他地物之间的区分是研究的核心和难点。为提高建筑物与其他地物在机载激光点云中的区分能力,提出了一种建筑物点云层次提取方法。首先,在点云滤波后,从非地面点云中提取建筑物候选区域;然后,通过形态学重建和点云平面分割方法对建筑物候选区域构建多尺度空间,并建立目标区域的拓扑关系图;最后,在拓扑关系图基础上,利用5种特征量对目标区域分类,并精确提取建筑物点云。为了测试算法的有效性和可靠性,利用国际摄影测量与遥感学会（International Society for Photogrammetry and Remote Sensing,ISPRS）提供的Vaihingen和Toronto两组测试数据集进行实验,并由ISPRS对结果进行评估,其中基于面积和目标的完整度、正确率和提取质量分别都大于87.8%、94.7%、87.3%。与其他建筑物提取方法相比,该方法在基于面积和目标的质量指标方面最为稳定。实验结果表明,在不同的城市场景下,该算法能够稳健地提取建筑物,并保持很高的正确率。 相似文献
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Segmentation of mobile laser point clouds of urban scenes into objects is an important step for post-processing (e.g., interpretation) of point clouds. Point clouds of urban scenes contain numerous objects with significant size variability, complex and incomplete structures, and holes or variable point densities, raising great challenges for the segmentation of mobile laser point clouds. This paper addresses these challenges by proposing a shape-based segmentation method. The proposed method first calculates the optimal neighborhood size of each point to derive the geometric features associated with it, and then classifies the point clouds according to geometric features using support vector machines (SVMs). Second, a set of rules are defined to segment the classified point clouds, and a similarity criterion for segments is proposed to overcome over-segmentation. Finally, the segmentation output is merged based on topological connectivity into a meaningful geometrical abstraction. The proposed method has been tested on point clouds of two urban scenes obtained by different mobile laser scanners. The results show that the proposed method segments large-scale mobile laser point clouds with good accuracy and computationally effective time cost, and that it segments pole-like objects particularly well. 相似文献
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针对利用TM影像进行土地利用变化分析的目标,提出一种基于控制点自动影像匹配的影像数据库建库及自动更新方法。以武汉城区1998年、2002年两个时期TM影像为试验区,从影像控制点数据库建库方法、影像控制点搜索方法和影像控制点自动更新方法三个方面展开研究。研究表明,上述方法可行,具有较好的实用价值和可操作性。 相似文献
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从卫星遥感全色图像中自动提取城市目标 总被引：11，自引：0，他引：11
提出了一种从卫星遥感全色图像中自动提取城市目标的方法。在总结城市目标的卫星遥感全色图像特性的基础上 ,设计了一种层次提取的方法。首先在低分辨率图像中提取城市目标的候选区域 ;接着在候选区域内利用城市目标一些更复杂的特性在高分辨率图像中证实城市目标。为了获得城市目标的边界 ,提出了一种基于边缘点密度的算法 ,并将算法应用去提取SPOT图像中的城市目标 ,取得了较好的试验结果 相似文献
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利用机载LiDAR点云数据进行建筑物重建是当今摄影测量与遥感领域的一个热点问题,特别是复杂形状建筑物模型的精确自动构建一直是一个难题。本文提出一种基于关键点检测的复杂建筑物模型自动重建方法,采用RANSAC法与距离法相结合的分割方法自动提取建筑物屋顶各个平面的点云,并利用Alpha Shape算法提取出各个平面的精确轮廓,根据屋顶平面之间的空间拓扑关系分析建筑物的公共交线特征,在此特征约束下对提取的初始关键点进行修正,最终重建出精确的建筑物3维模型。选取不同类型复杂建筑物与包含复杂建筑物的城市区域点云进行实验,结果表明该算法具有较强实用价值。 相似文献
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在基于倾斜影像的城市场景重建过程中,由于获取影像时存在场景遮蔽和大视点变化的情况,建筑物立面等区域存在着影像密集匹配点云稀疏甚至空洞的情况,自动化重建难度大,难以反映建筑物的真实形态。本文提出了一种新的基于倾斜影像的城市场景隐式曲面重建方法：首先,以倾斜影像密集匹配点云为基础建立Delaunay四面体;然后,对Delaunay四面体进行约束图割,提取出可视化的三角面,进而更加精确地估计点云的法向信息;最终,结合Screened Poisson曲面重建,实现了城市场景的隐式曲面重建。通过多种隐式曲面重建方法的对比试验,验证了本方法的准确性和适用性。 相似文献
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高分辨率遥感影像建筑物分级提取 总被引：1，自引：1，他引：0
高分辨率遥感影像建筑物信息自动提取是遥感应用研究中的一个热点问题,但由于受到成像条件不同、背景地物复杂、建筑物类型多样等多个因素的影响使得建筑物的自动提取仍然十分困难。为此,在综合考虑影像光谱、几何与上下文特征的基础上,提出了一种基于面向对象与形态学相结合的高分辨率遥感影像建筑物信息分级提取方法。该方法首先利用影像的多尺度及多方向Gabor小波变换结果提取建筑物特征点;然后采用面向对象的思想构建空间投票矩阵来度量每一个像素点属于建筑物区域的概率,从而提取出建筑物区域边界;最后在提取的建筑物区域内应用形态学建筑物指数实现建筑物信息的自动提取。实验结果表明,本文方法能够高效、高精度地完成复杂场景下的建筑物信息提取,且提取结果的正确性和完整性都优于效果较好的PanTex算法。 相似文献
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提出了两种基于圆形的单幅图像平面几何量测方法。第一种算法首先计算出与待测对象平行的直径,然后获得圆形所在平面上任意两点之间的距离。受待测线段位置、方向等影响,量测结果的精度各向差异大。第二种算法首先求取圆形的外接正方形,将问题转化为包含正方形的平面距离量测。模拟图像与真实图像的测试结果表明,第二种算法的量测精度更具有稳定性。 相似文献
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高分辨率遥感影像具有场景复杂、目标种类多样、同一目标呈现多种形态等特点,给建筑物检测带来困难。近年来,可变形部件模型（deformable part model,DPM）被广泛应用到模式识别领域,并且在自然场景的目标识别方面取得很好的效果。结合可变形部件模型,提出一种针对高分辨率遥感影像中建筑物的检测方法,将建筑物看作可变形部件的组合,通过训练得到其对应的参数模板,并采用滑动窗口的方式遍历待检测的影像,判断其中是否存在建筑物目标。通过对分辨率为0.5 m的高分辨率遥感影像的实验证明了方法的有效性。 相似文献
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建筑场景三维重建中影像方位元素的获取方法 总被引：15，自引：3，他引：15
基于影像的三维重建需要确定影像的内、外方位元素，影像中的灭点为其提供了重要的线索，但灭点位置的不确定性，影响了方位元素计算的结果。通过分析灭点几何，建立了影像直线段与方位元素的直接联系，根据最小二乘平差的有关理论，给出了迭代计算影像的内、外方位元素的方法，并在三维重建的实践中进行了验证。 相似文献
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Jeffrey Shan 《The Photogrammetric Record》2001,17(98):343-353
This paper describes an approach to single image automatic orientation and point determination by using current ortho-images and a DTM, and the experience gained in its implementation. The procedure proposed automatically extracts and matches feature points in evenly distributed patches on aerial images and ortho-images. A large number of image measurements (up to several thousand) are obtained in this process and are included in a robust space resection to determine the orientation parameters of the aerial image. For point determination with a single image, a method is formalised which integrates the DTM interpolation into the space resection so that the 3D ground coordinates of the image points can be determined in a unified mathematical model. Tests and analyses of this method show that the large number of automatic image measurements relieves the requirement for complicated and precise feature extraction and matching methods. The ground points obtained from single image intersection have an accuracy of approximately 1 pixel in planimetry, which fulfils the requirement for ortho-image updating. The elevation accuracy is mainly dependent on the quality of the current DTM and the interpolation method applied to it. 相似文献
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提出了一种低空无人机(unmanned aerial vehicle,UAV)序列影像与激光点云自动配准的方法。首先分别基于多标记点过程与局部显著区域检测对激光点云和序列影像的建筑物顶部轮廓进行提取,并依据反投影临近性匹配提取的顶面特征。然后利用匹配的建筑物角点对,线性解算序列影像外方位元素,再使用建筑物边线对的共面条件进行条件平差获得优化解。最后,为消除错误提取与匹配特征对整体配准结果的影响,使用多视立体密集匹配点集与激光点集进行带相对运动阈值约束的ICP(迭代最临近点)计算,整体优化序列影像外方位元素解。试验结果表明本文方法能实现低空序列影像与激光点云像素级精度的自动配准,联合制作DOM精度满足现行无人机产品1∶500比例尺标准。 相似文献
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多尺度分割的高分辨率遥感影像变化检测 总被引：4，自引：1，他引：3
针对高空间分辨率的遥感影像,提出了一种基于多尺度分割的变化检测算法。采用Mean-Shift分割算法对影像进行多尺度分割,构建了不同尺度上的地理对象,以不同尺度上的地理对象灰度均值构建了变化检测的多尺度特征向量,采用变化矢量分析法获得最后的变化检测结果。以城镇区和农田区的Quick Bird影像对本文算法进行了检验,从精度评价的效果来看,无论城镇区还是农田区,采用面向对象的变化检测方法精度都高于基于单像素的检测方法,且当尺度层数固定时,多尺度组合的变化检测结果优于单一尺度的变化检测结果,对城镇、农田区域的变化检测的精度分别达到87.57%和81.55%。本文算法既可以顾及大面积同质区域变化,又可以反映小的地物目标及边缘部分的变化,能够很好地满足城镇、农田等不同环境背景下的变化检测需求,在国土资源监测中具有一定的应用价值。 相似文献
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We propose an automatic and robust approach to detect, segment and classify urban objects from 3D point clouds. Processing is carried out using elevation images and the result is reprojected onto the 3D point cloud. First, the ground is segmented and objects are detected as discontinuities on the ground. Then, connected objects are segmented using a watershed approach. Finally, objects are classified using SVM with geometrical and contextual features. Our methodology is evaluated on databases from Ohio (USA) and Paris (France). In the former, our method detects 98% of the objects, 78% of them are correctly segmented and 82% of the well-segmented objects are correctly classified. In the latter, our method leads to an improvement of about 15% on the classification step with respect to previous works. Quantitative results prove that our method not only provides a good performance but is also faster than other works reported in the literature. 相似文献