3d Point Cloud Data Processing Applications

Laser scanning technology is a recent development of data collection hot spot. Because it has peediness, penetrability, not sex, real time characteristic, dynamics, initiative, digital characteristics, high precision, high density, high efficiency and many other traditional routine measurement techniques do not providing, So it is widely used in many fields, having wide development prospects and application requirements. For examplej,it's used in 3d modeling, engineering survey, disaster monitoring, historical and cultural relic protection and so on. But point cloud data obtain too mang points, has many bad points, so that it is disadvantageous to the storage and transmission, going against the follow-up. So the point cloud data processing becomes especially important. The point cloud data processing includes multiple aspects. This paper mainly studies point cloud data processing, the compact, denoising and light data smoothly, coding compression.In this thesis first reviewed the 3d laser scanning measurement technology development history and research status, and introduces various 3d laser scanner, summarized the 3d laser scanning of measuring technology of main application fields, introduces'in detail the ground 3d laser scanning measurement system composed and working principle of the system, and several manufacturers 3d laser scanner's main technical characteristic comparison. Secondly, based on measuring data processing, digital image processing and the geographic information system based on knowledge disciplines such as discussed for terrestrial laser scanning original data data downsizing and denoising and light shun, coding compressed problem. Analyzed the denoising commonly used method, and based on this, advances the method that based on the eligibility c-means bilateral filtering de-noising and the grid nets - fitting plane method denoising. The streamlined for data compression, combined with of the existing research results, this paper puts forward the regional center compression method and eligibility curvature mixed sampling method. And, use matlab software to realize point cloud data processing. Through the experimental results, continuously improve some methods, finally obtained the ideal point cloud data and prepare for the follow-up.