基于渐进形态学开运算和偏度平衡法的LiDAR数据滤波方法

Li DAR Data Filtering Method Based on Progressive Morphological Open Operation and Skewness Balancing Method

基于高程的偏度参数统计的Li DAR数据滤波对地形起伏城区滤波适应性不强的弱点,对该方法进行了改进,提出了结合渐进形态学开运算和偏度平衡法的Li DAR数据滤波方法,该方法的原理就是将所有引起高程的突变转换成全由植被、建筑等非地面点引起,而不是由地形高程引起的,这个转换的中间量就是高差,即将高差作为偏度系数的统计对象。并通过实验验证了该方法的合理性,实验结果表明,改进的方法不仅延续了参数统计法无需阈值的优势,而且对城区滤波更具适应性、合理性和稳定性,能够明显地提高滤波精度。

The filtering method based on the statistical skewness parameters of LiDAR elevation data is not strong for adapting filtering urban topography , and the improved method is based on progressive morphological open operation and skewness balancing method. The principle of the method is that caused by the elevation of mutations translate into non - ground point such as vegetation and buildings, rather than the terrain elevation. This intermediate quantity of transformation is elevation difference that is skewness coefficient statistics object. The results show that the improved method is not only the continuation of the advantages of parametric statistical methods without threshold, but more adaptive, rationality and stability for filtering of the city, this method can significantly improve filtering accuracy.