Acta Optica Sinica, Volume. 37, Issue 12, 1210003(2017)

Three-Dimensional Point Cloud Compression Algorithm Based on Improved Octree

Yuan Huang1,2、*, Feipeng Da1,2, and Lin Tang1
Author Affiliations
  • 1 School of Automation, Southeast University, Nanjing, Jiangsu 210096, China
  • 2 Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, Nanjing, Jiangsu 210096, China
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    Aim

    ing at the transmission and storage requirements of three-dimensional model in the large data environment, a three-dimensional point cloud lossy compression algorithm based on the octree is presented. The stop condition of the octree segmentation is improved, so the segmentation can be stopped at an appropriate depth, and the proper size of voxel is ensured. At the same time,the K neighborhood is established based on the segmentation and the outliers of original point cloud are removed by simple and effective statistical method. In the data structure, each node is assigned to a bit mask. The data query and manipulation are traversed by manipulating the bit mask. Then the subsequent point position coding are optimized. The proposed algorithm effectively removes the outliers and miscellaneous points on the surface, and improves the efficiency of point cloud compression in range encoding. The experimental results show that this algorithm can preserve the key information of three-dimensional point cloud data more completely, obtain a good compression rate and shorten compression time.

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    Yuan Huang, Feipeng Da, Lin Tang. Three-Dimensional Point Cloud Compression Algorithm Based on Improved Octree[J]. Acta Optica Sinica, 2017, 37(12): 1210003

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    Paper Information

    Category: Image Processing

    Received: Jul. 3, 2017

    Accepted: --

    Published Online: Sep. 6, 2018

    The Author Email: Huang Yuan (whhbb@163.com)

    DOI:10.3788/AOS201737.1210003

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