According to analysis of the limitations of traditional algorithms

such as local points fitting and frequency domain signal analysis

a typical noise removalremoval algorithm of LIDAR point clouds based on three-dimensional finite-element analysis is proposed. Firstly

point clouds is partitioned into smaller and similar units by finite elements named space hexahedron model. And then

all of the units are classified into noise units or non-noise units with adjacency-based reasoning rules. Finally

the low noise is removed by iterative processing with finer threshold. In this approach

we did experiments with a real strip data which is obtained by an international mainstream system. The result shows that finite-element analysis has good performance in noise removal.