Research On Points Cloud Thinning Algorithm For Airborne LiDAR Data

Airborne LiDAR(Light Detection And Ranging,LiDAR)is a new active earth observing system with the laser for detection means,this technology has had a major breakthrough in the real-time acquisition of three-dimensional space information,and it provides a new survey tool for collec ting high density and high accuracy terrain data.At present,LiDAR can collect very dense data with the progress of hardware.On the one hand,it can provide a rich surface de tails;on the other hand,it also brings a lot of data redundancy that make trouble for data processing and information analysis,so this paper studies the LiDAR data thinning algorithms.Summarizes the main features of airborne LiDAR data,and analyzes the organization and management of point cloud data.LiDAR·data thinning algorithms are researched and summarized detailed in this paper.Based on this,a new thinning algorithm is brought forward based on surface variation.And design a PSNR model to qualitatively and quantitatively analyse the thinning result.The experiments are carried out using various LiDAR data thinning algorithms.The results of experiments show that the thinning algorilful based on surface variation can betei reduce terrain redundant data and keep information on terrain features,and can discretionarily control compression ratio.So,it has important practical value.