首页|GeoSLAM激光点云的三维可视化数字影像融合目标细部重建

GeoSLAM激光点云的三维可视化数字影像融合目标细部重建

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三维激光扫描技术应用范围逐渐扩大,但激光点云缺乏真实的纹理信息,致使目标细部重建与实际目标存在偏差,而三维可视化数字影像技术可以有效地弥补三维激光扫描技术的不足,如何对其进行有效融合应用成为重点研究方向,故提出GeoSLAM激光点云的三维可视化数字影像融合目标细部重建方法研究。利用点云滤波算法去除GeoSLAM激光点云中的噪声信息,校正处理三维可视化数字影像的畸变现象,以此为基础,利用Moravec算子提取融合目标细部特征点,配准激光点云与数字影像中的特征点,制定融合目标细部重建程序,从而实现激光点云与数字影像的有效融合,即目标细部的精准重建。实验结果显示:本方法能够更加精准地完成细部重建,相比对比方法而言,具备均值为0。929 5的相关系数,和更低的融合目标细部特征点提取错误率,且对建筑类别的数字影像的细部重建效果更好,细部特征点提取错误率仅为1%,充分证实了提出方法应用性能更佳。
3D Visualization of GeoSLAM laser point cloud for digital image fusion and target detail reconstruction
The application scope of 3D laser scanning technology is gradually expanding,but the lack of real tex-ture information in laser point clouds results in deviation between target detail reconstruction and actual targets.3D vi-sualization digital imaging technology can effectively compensate for the shortcomings of 3D laser scanning technology.How to effectively integrate and apply it has become a key research direction,Therefore,a study on the 3D visualiza-tion digital image fusion target detail reconstruction method of GeoSLAM laser point cloud is proposed.Using the point cloud filtering algorithm to remove noise information from the GeoSLAM laser point cloud,and correcting and process-ing the distortion phenomenon of 3D visualization digital images,based on this,the Moravec operator is used to extract the detailed feature points of the fusion target,register the feature points in the laser point cloud and digital images,and develop the fusion target detail reconstruction program,thus achieving effective fusion of the laser point cloud and digital images,that is,precise reconstruction of the target details.The experimental results show that:Compared with the comparison methods,the proposed method can complete the detail reconstruction more accurately.It has an aver-age correlation coefficient of 0.929 5,and a lower error rate of detail feature point extraction of the fusion target.The detail reconstruction effect of the digital image of the architectural category is better,and the error rate of detail feature point extraction is only 1%,which fully confirms the better application performance of the pro-posed method.

digital imaging3D visualizationdetailed reconstructionintegration objectivesGeoSLAM laser point cloud

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郑州科技学院,郑州 450000

数字影像 三维可视化 细部重建 融合目标 GeoSLAM激光点云

河南省社科联项目郑州市社科联项目河南省教育科学规划课题

SKL-2021-1196ZSJX202210522020YB0337

2024

激光杂志
重庆市光学机械研究所

激光杂志

CSTPCD北大核心
影响因子:0.74
ISSN:0253-2743
年,卷(期):2024.45(7)