【摘 要】
：
Aimed at deficiency of algorithms based on traditional statistics method,this paper proposed a gross error detection and removal algorithm for LiDAR point c
【机 构】
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Engineering University of CAPF,Graduate Management Group,Xi'an,710086
【出 处】
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The 6th International Symposium on Larger Asian River(第六届亚洲大
论文部分内容阅读
Aimed at deficiency of algorithms based on traditional statistics method,this paper proposed a gross error detection and removal algorithm for LiDAR point cloud based on robust mahalanobis distance.First,LiDAR point cloud is divided into several blocks.Then,DetMCD (Deterministic Minimum Covariance Determinant) algorithm is performed to get robust estimation of the position and scale parameters of each block.With those parameters,robust mahalanobis distance of each point within the block is calculated.As the square of robust mahalanobis distance can be considered to obey Chi-square distribution,the gross error discrimination threshold can be obtained with certain confidence.Finally,gross errors are detected and removed with the threshold and robust mahalanobis distance in each block.
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