基于单光子探测的LiDAR三维点云数据处理方法设计
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摘要
针对移动曲面拟合法在处理三维点云数据时需要人为干预阈值的主要缺点,引入数学形态学的腐蚀运算,在处理采用TCSPC技术的机载激光测绘雷达获取的曲面目标物形成的三维点云数据的背景下,提出了"基于数学形态学改进的移动曲面拟合算法"。同时,为了提高数据利用效率,避免信息丢失,提出了"先去噪,再补点,后迭代"的去噪处理思想,在不降低数据密度的情况下,高效、稳健地进行噪声处理,在噪声水平为50%的情况下,总误差可以降至3.9%。
It introduce the corrosion of mathematical morphology operations,puts forward the "improved moving surface denoising algorithm based on mathematical morphology",in view of the major drawback that the threshold of moving curved surface fitting need for human interventionwhen processing three-dimensional point cloud data.The mothed is suitable for the three-dimensional point cloud data of surface target accessing from LiDAR with TCSPC technique.At the same time,in order to improve the efficiency of data utilization and avoid the loss of information,a new denoising approach of "first to remove noise,then iteration after patch" is established.And without reducing the data density,the noise is processed efficiently and stably.Finally,through the experiment,the total error can be reduced to 3.9% when the noise level is 50%.
It introduce the corrosion of mathematical morphology operations,puts forward the "improved moving surface denoising algorithm based on mathematical morphology",in view of the major drawback that the threshold of moving curved surface fitting need for human interventionwhen processing three-dimensional point cloud data.The mothed is suitable for the three-dimensional point cloud data of surface target accessing from LiDAR with TCSPC technique.At the same time,in order to improve the efficiency of data utilization and avoid the loss of information,a new denoising approach of "first to remove noise,then iteration after patch" is established.And without reducing the data density,the noise is processed efficiently and stably.Finally,through the experiment,the total error can be reduced to 3.9% when the noise level is 50%.
引文
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[2]陈兆东.多通道时间相关单光子计数技术的研究[D].哈尔滨:哈尔滨工业大学,2013.
[3]杨东雄.供热管理平台中数据甄别与工况研判的应用研究[D].大连:大连海事大学,2015.
[4]罗伊萍,姜挺,龚志辉,等.基于自适应和多尺度数学形态学的点云数据滤波方法[J].测绘科学技术学报,2009,26(6):426-429.
[5]隋立春,张熠斌,柳艳,等.基于改进的数学形态学算法的LiDAR点云数据滤波[J].测绘学报,2010,26(13):210-211.
[6]LINDENBERGER J.Laser-profilmessungen zur topographischen gelandeaufnahme[D].Munich:Deutsche Geodtische Commission,1993.
[7]ZHANG K,CHEN S C,WHITMAN D,et al.Aprogressive morphological filter for removing nonground measurements from airborne LIDAR data[J].IEEE Transactions on Geoscience&Remote Sensing,2003,41(4):872-882.
[8]WHITMAN D,ZHANG K.Comparison of three algorithms for filtering airborne Lidar data[J].Photogrammetric Engineering&Remote Sensing,2005,71(3):313-324.
[9]尚大帅,马东洋,赵羲,等.一种基于移动曲面拟合的机载LIDAR点云数据滤波方法[J].测绘技术装备,2012(2):23-25.
[10]李崇瑞.DLG辅助的机载LiDAR点云数据滤波研究[D].太原:太原理工大学,2015.
[11]苗启广,史俊杰,刘天歌,等.一种快速生成DSM的不规则三角网构网新方法[J].系统工程与电子技术,2014,36(9):1868-73.
[12]张小红.机载激光雷达测量技术理论与方法[M].武汉:武汉大学出版社,2007.
[13]夏冰,苏国中,周梅,等.LIDAR点云中高精度建筑物分割算法研究[J].微计算机信息,2010,26(13):210-211.
[14]黄停.动态心电信号采集分析及系统研究[D].沈阳:东北大学,2013.
[15]包全福,龚亮,李正国.融合航空影像的LiDAR地物点云分类[J].测绘工程,2012,21(1):34-38.