Laser Point Cloud Data Compression To Streamline Research

With the development of the measurement technology, in the 1990 s, the 3 dimension laser scanning technology appeared. It is a high-tech technology and also is the focus of recent survey development. There are plenty of advantages of 3 dimension laser scanning technology compared with conventional measurement. It can scan object surface 3 d coordinate data fast and accurately, which is high speed, strong penetrating, the contact, real-time, dynamic, initiative, high precision, high density and high efficiency. It has been used in many fields, for example, digital city, measurement engineering, reverse engineering, protection of ancient architectural structures. Although the use of 3 d laser scanning technology can quickly get 3 d coordinate the surface of the object, it but get the coordinates of the scan data quantity is enormous. So the huge data against the computer storage and transmission and go against the follow-up of modeling work. So it is necessary to simplify point cloud data. The point cloud data processing includes many aspects. This paper mainly studies the simplify technology of cloud data processing. At the same time, it investigates reconstruction of the model and assesses the cloud data after the reconstruction. The researches list as follow:This paper introduces the current situation of 3d-laser scanning technology at home and abroad. It also describes the development of the point cloud data compression algorithm and introduces some of the 3 d laser scanner, their main areas of application, components of the system and working principle.In this paper, it indicates the point cloud data pretreatment process. It summarizes the noise of some point cloud data filtering method. It compared the three methods' the advantages and disadvantages and the applicable conditions.It studies minimum distance method in cloud data simplify and checked cloud data. It referred to simplify the cloudy with the size of point cloud model adjacent triangle's angles. Combining the minimum distance method and referred new method to reconstruct the triangle net using simplified cloud data through programming. It evaluates the quality using the volume difference between before and after downsizing, which compared the surface area to verify the feasibility of the volume method.In the matlab platform, we through the programming of a cloud data compression to obtain better result, preparing for cloud molding.