| The 3D laser scanning point cloud data with high precision,high sampling rate,access speed,is widely used in the field of cultural relics protection,industrial inspection,medical research and entertainment.It has an important research value for daily life and scientific research.In order to get a comprehensive understanding and further application of the laser scanning point cloud data through network under different operating systems,it is necessary to study the method of laser scanning point cloud data processing.This paper aims to remote visualization of 3D point cloud data,the key problems of the data organization,data compression and data scheduling are studied,and the specific work is as follows:In the first part,we study the method of 3D laser scanning point cloud data organization based on hierarchical bounding sphere structure.In order to effectively organize the 3D laser scanning point cloud data,firstly,the 3D laser scanning point cloud data is summarized,and the structure and characteristics of 3D laser scanning technology and point cloud data are introduced.Then,aiming at the remote visualization of 3D laser scanning point cloud data,the related technologies of cloud data organization are studied.Finally,3D laser scanning point cloud data is organized using hierarchical bounding sphere structure.In the second part,the method of 3D laser scanning point cloud data compression based on gray value coding is studied.In order to reduce the storage space of 3D laser scanning point cloud data and the amount of data transmitted in the visualization,firstly,the existing 3D laser scanning point cloud data compression method is analyzed and compared in detail.Then according to the existing compression algorithm based on virtual structure light projection system required a large number of bits,we proposed a compression method of 3D laser scanning point cloud data based on gray value encoding.This method can reduce the image bits needed to store the 3D laser scanning point cloud data and improve the point cloud data compression ratio.In view of the advantages and disadvantages of different dithering algorithms in 3D laser scanning point cloud data compression,the compound dithering algorithm is proposed.In order to reduce the reconstruction error,the data compression of 3D laser scanning point cloud data is realized,and the data compression ratio is improved.In the third part,we study the data scheduling method based on image hierarchical bounding ball structure.In order to avoid the point cloud data transmission which is not related to the final visualization,the visibility judgment method based on visual field is studied.In order to transmit the data with high precision,the hierarchical selection method of multi-level data is studied.According to the image compression method and hierarchical structure,the image bounding sphere structure built by using image interpolation algorithm is proposed.The scheduling method using sight visibility determination and level selection method is proposed.The fourth part studies the remote visualization of 3D laser scanning point cloud data.In order to meet the requirements of the application of 3D laser scanning point cloud data in cross platform,real time and high frame frequency,a visualization framework for 3D laser scanning point cloud data based on browser/server structure is established.First determine the objectives and functional requirements of visualization framework;secondly according to the object the design criterion of the framework is determined,and determine the overall structure of the framework and according to the flow of visualization of 3D laser scanning point cloud data;then each module are realized;finally experiments on specific 3D laser scanning point cloud data verify the effectiveness of the proposed framework. |
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