水深测量
回声测深
遥感
激光雷达
稳健性(进化)
均方误差
计算机科学
点云
地质学
地理
数学
人工智能
统计
地图学
生物化学
化学
基因
作者
Xiankun Wang,Fanlin Yang,Hande Zhang,Dianpeng Su,Zhiliang Wang,Fangzheng Xu
出处
期刊:IEEE Geoscience and Remote Sensing Letters
[Institute of Electrical and Electronics Engineers]
日期:2022-01-01
卷期号:19: 1-5
标识
DOI:10.1109/lgrs.2021.3076462
摘要
Airborne light detection and ranging (LiDAR) bathymetry (ALB) and multibeam echo sounder (MBES) are both active remote sensing technologies that are complementary in terms of survey scope. The registration of ALB and MBES data can provide complete overwater and underwater geoinformation on a measurement target. However, in the overlapping area of the ALB and MBES data, there are different point densities and few identifiable structure features. Although the existing multiplatform registration strategies can provide good results for overwater datasets, they are difficult to adapt for the registration of ALB and MBES data. Therefore, to address these problems, a new registration method for ALB and MBES datasets is proposed in this letter. First, a triangulated irregular network (TIN) is constructed with control points extracted from the MBES data. Then, the features of the TIN facets are extracted to identify the data gaps. Finally, the transformation parameters are iteratively calculated by minimizing the distances between the ALB points and MBES TIN facets. Five samples with different characteristics captured around Yuanzhi Island in the South China Sea are selected to evaluate the performance of the proposed method. The mean root mean square error (RMSE) of the five samples is approximately 0.2 m. The results indicate that the proposed method performs well for the registration of ALB and MBES datasets, with advantages in accuracy and robustness.
科研通智能强力驱动
Strongly Powered by AbleSci AI