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JBE, vol. 26, no. 5, pp.553-565, September, 2021
Comparative Experiment of 2D and 3D DCT Point Cloud Compression
Kwijung Nam, Junsik Kim, Muhyen Han, Kyuheon Kim, and Minkyu Hwang
C.A E-mail: email@example.com
Point cloud is a set of points for representing a 3D object, and consists of geometric information, which is 3D coordinate information, and attribute information, which is information representing color, reflectance, and the like. In this way of expressing, it has a vast amount of data compared to 2D images. Therefore, a process of compressing the point cloud data in order to transmit the point cloud data or use it in various fields is required. Unlike color information corresponding to all 2D geometric information constituting a 2D image, a point cloud represents a point cloud including attribute information such as color in only a part of the 3D space. Therefore, separate processing of geometric information is also required. Based on these characteristics of point clouds, MPEG under ISO/IEC standardizes V-PCC, which imitates point cloud images and compresses them into 2D DCT-based 2D image compression codecs, as a compression method for high-density point cloud data. This has limitations in accurately representing 3D spatial information to proceed with compression by converting 3D point clouds to 2D, and difficulty in processing non-existent points when utilizing 3D DCT. Therefore, in this paper, we present 3D Discrete Cosine Transform-based Point Cloud Compression (3DCT PCC), a method to compress point cloud data, which is a 3D image by utilizing 3D DCT, and confirm the efficiency of 3D DCT compared to V-PCC based on 2D DCT.
Keyword: Point cloud, 3D DCT
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