Chen Chuanfa, Li Yanyan, Zhao Na, Guo Jinyun, Liu Guolin
State Key Laboratory of Mining Disaster Prevention and Control Co-founded by Shandong Province and the Ministry of Science and Technology, Shandong University of Science and Technology, Qingdao, China.
Shandong Provincial Key Laboratory of Geomatics and Digital Technology of Shandong Province, Shandong University of Science and Technology, Qingdao, China.
PLoS One. 2017 May 3;12(5):e0176954. doi: 10.1371/journal.pone.0176954. eCollection 2017.
A fast and robust interpolation filter based on finite difference TPS has been proposed in this paper. The proposed method employs discrete cosine transform to efficiently solve the linear system of TPS equations in case of gridded data, and by a pre-defined weight function with respect to simulation residuals to reduce the effect of outliers and misclassified non-ground points on the accuracy of reference ground surface construction. Fifteen groups of benchmark datasets, provided by the International Society for Photogrammetry and Remote Sensing (ISPRS) commission, were employed to compare the performance of the proposed method with that of the multi-resolution hierarchical classification method (MHC). Results indicate that with respect to kappa coefficient and total error, the proposed method is averagely more accurate than MHC. Specifically, the proposed method is 1.03 and 1.32 times as accurate as MHC in terms of kappa coefficient and total errors. More importantly, the proposed method is averagely more than 8 times faster than MHC. In comparison with some recently developed methods, the proposed algorithm also achieves a good performance.
本文提出了一种基于有限差分TPS的快速稳健插值滤波器。该方法采用离散余弦变换，在网格数据情况下高效求解TPS方程的线性系统，并通过针对模拟残差的预定义权重函数，减少异常值和误分类的非地面点对参考地面构建精度的影响。采用国际摄影测量与遥感学会（ISPRS）委员会提供的15组基准数据集，将该方法的性能与多分辨率分层分类方法（MHC）进行比较。结果表明，在kappa系数和总误差方面，该方法平均比MHC更准确。具体而言，该方法在kappa系数和总误差方面分别是MHC的1.03倍和1.32倍。更重要的是，该方法平均比MHC快8倍以上。与一些最近开发的方法相比，该算法也具有良好的性能。
