共查询到17条相似文献,搜索用时 140 毫秒
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随着Li DAR的迅速发展,三维激光扫描技术已经被广泛运用于各个领域。点云数据配准过程中,传统的配准算法比较依赖特征点匹配精度,粗差点的存在会较大程度地影响配准精度和配准效率。通过对罗德里格矩阵、整体最小二乘原理的分析,提出了一种基于整体最小二乘的罗德里格矩阵算法。在该算法实现的过程中,能够考虑到系数矩阵误差,降低算法实现过程中特征点坐标误差对参数求解的影响。实验结果表明,本文算法比参数算法和严密的罗德里格算法精度更高、稳定性更强,在初始对应点坐标误差较大的情况下仍能获得精度较为稳定的变换参数。 相似文献
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受船载仪器、海况等要素限制,传统水深测量中浅水区域无法对浅海水深进行测量。为克服此困难,利用近年来新兴的机载激光测深系统(light detection and ranging system,简称LiDAR)进行浅海水深测量,用LiDAR获取的点云数据进行处理后得到的水下地形等深线与海图图载水深进行直观对比,同一坐标点下的点云水深与截图水深进行定量分析。结果表明,LiDAR获取的水深精度高,水深点密集,可更快获得浅海区域详细的高精度的水下地形。这些优点使其在近岸浅海海岸防护、围海造田、港口建设等海洋工程项目中应用前景广阔。此外目前国内LiDAR技术主要用于陆地,应用于浅海水深测绘还很少,本研究对机载LiDAR进行水深测量的研究进行了补充。 相似文献
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三维点云数据拼接中ICP及其改进算法综述 总被引:5,自引:0,他引:5
ICP算法是三维点云数据精确拼接过程中的主流算法.文章对目前国内外ICP及其各种改进算法的发展现状进行了系统地分析与研究.将ICP算法分为4个主要阶段:(1) 对原始点云数据进行采样;(2) 确定初始对应点集;(3) 去除错误对应点对;(4) 坐标变换的求解.分别对各个阶段中典型方法的基本思想和关键技术进行了分类与分析,并在精度与效率等方面对这些算法进行了比较.最后对目前算法研究中的难点问题及未来的研究重点进行了展望. 相似文献
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针对水下多波束地形测量点云去噪问题,提出了一种基于阈值自适应确定的点云滤波算法。首先引入虚拟网格对多波束点云进行分区编号,并采用二次分层统计法剔除显著离群噪点;其次归一化计算网格内种子点与邻域各点的坡度角,引入k-Medoids聚类算法自适应更新坡度阈值;最后按照多尺度滤波窗口逐级对点云进行迭代运算,得到精细化地形点云。2个实验区的多波束点云滤波实验结果表明,本文算法能较好去除多波束点云的噪声和非地形点,有效提高坡度阈值的自适应性,滤波精度有明显提升,可以适用于大规模的多波束点自动化云滤波工作。 相似文献
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为提高多波束数据处理的准确性和简便性,研究了多波束水深点云处理的策略和关键算法,构建了kd-tree(k-dimensional tree)结构加速点云查找,针对大尺度噪点设计了半径滤波和统计滤波算法,针对小尺度噪点提出了双边滤波算法,并对以上算法的适用性进行了探讨分析。实验结果表明,当设置适合的滤波阈值,半径滤波和统计滤波能高效去除大尺度噪点,且保留地形特征,总误差分别为2.25%和2.76%。在大尺度噪点去除的基础上,改进的双边滤波可以实现地形平滑的同时,保持水深点云的有效数据量。研究成果为多波束点云数据的自动化处理提供了解决方案,对多波束测量工作的效果和效率提升做了有益尝试。 相似文献
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ICESat-2卫星搭载先进的光子计数式激光雷达ATLAS,使用全新的测量方式获取海量的光子点云数据.光子计数激光点云由于受海洋表面噪声以及水中穿透性较强等因素影响,现有的去噪算法在浅海区域海面去噪上存在一定的局限性.针对上述问题,本文提出了一种基于改进DBSCAN参数的去噪算法,通过利用点云数据集自身分布特性生成候选Eps参数,自动寻找最优Eps参数,改进现有的DBSCAN去噪算法,并在南海两处岛礁区域进行实验验证.实验表明该算法在浅海区域的去噪精度达到98%,优于传统算法的去噪精度,该研究可为ICESat-2海面点的去噪工作提供参考. 相似文献
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Shengming Hu Zhijian Chen Chenghui Wan Chun Tang Wen Xiong 《Marine Georesources & Geotechnology》2020,38(4):385-392
AbstractCompared with traditional methods, the three-dimensional laser-scanning (3D-LS) technique can efficiently acquire many high-quality geometric properties of rock discontinuities. In practice, engineers usually prefer to simplify the processing by using single-station point data and roughly orienting owing to the complexity of registration/georeferencing multi-station point data. However, prior published studies have paid little attention to the accuracy and reliability when determining discontinuity orientations using 3D-LS. We propose a reliable and accurate method with robust on-site applicability. As part of an ongoing effort, we are evaluating the precision of the commonly used coarse registration method and the fine registration method, and promoted the optimized coarse- and fine-registration methods and evaluated their precision. It is found that: (1) the common and the optimized registration method can meet our project’s engineering requirements, and the optimized registration method improved accuracy in the dip direction by approximately 1°; (2) fine registration using an iterative closest point (ICP) algorithm can correct both dip direction and dip angle; and (3) the orientation is of high precision with commonly used coarse and fine registration, whereas the optimization effect to correct the orientation is slightly limited. 相似文献
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随着机器学习算法的不断更新发展,加之其良好的适应性、准确性及鲁棒性,在三维物体识别领域获得了广泛的应用,成为当前点云处理的研究热点。首先,本文对三维物体点云数据识别及机器学习的发展应用进行归纳。然后,从特征选择、特征提取、特征识别三个方面,进行分析总结。最后,指出机器学习在基于点云的三维物体识别领域的应用目前所面临的挑战及进一步研究的方向。 相似文献
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Shengming Hu Zhijian Chen Chenghui Wan Lei Huang 《Marine Georesources & Geotechnology》2013,31(10):1196-1204
AbstractWith the aid of three-dimensional laser scanning (3D-LS), a lot of geometric properties of rock discontinuities can be derived from the point cloud data. Due to the complexity of registration and georeferencing of multi-station point data, geological engineers tend to simplify processing by using single-station point data and orienting coarsely. However, there is a lack of accuracy and reliability study in the identification of discontinuity orientations with 3D-LS using different registration/georeferencing modes. In this study, the single-station scanning without registration/georeferencing was applied first to examine the accuracy and reliability of the scanner’s built-in direction system. After that, two types of automated registration/georeferencing modes were examined for the accuracy in rock mass discontinuity analysis. The results show that the dip angle measured by the scanner’s built-in directional system is reliable, accurate and can meet engineering requirements, while the dip direction measured by the scanner’s built-in directional system is unreliable and inaccurate. The dip direction is consistent but inaccurate through the semi-automated registration using natural point features and georeferencing by the scanner’s built-in directional system. Only through real-time kinematic (RTK) registration/georeferencing can the dip direction be reliable and accurate. It is observed that orientations captured by 3D-LS can be more accurate with RTK registration/georeferencing than manual survey. 相似文献
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针对卫星遥感技术在对滨海湿地互花米草监测时受分辨率、气候条件等多种因素限制存在一定局限性且通过单一的影像数据提取互花米草时精度不稳定的问题,提出了基于无人机点云与影像融合的面向对象互花米草提取方法。以黄河三角洲自然保护区为研究对象,获取了该区域的点云和多光谱影像。先将地面滤波后提取的植被点云与多光谱影像进行特征组合优化,然后对融合影像采用FNEA算法进行多尺度分割后采用基于改进的最近邻算法进行面向对象分类,最终得到的互花米草生产者精度和用户精度分别达到了82.53%和86.43%,较未融合点云的提取精度分别提高了22.34%和7.66%,分类结果的总体精度从89.54%提升至92.61%,且融合点云后影像能够有效区分两种生长状态的互花米草,表明本文提出的方法能够有效提高互花米草的提取精度。 相似文献