用于高效、轻量级点云压缩的低复杂度补丁投影法

IF 1.3 4区 计算机科学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC
Sungryeul Rhyu, Junsik Kim, Gwang Hoon Park, Kyuheon Kim
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引用次数: 0

摘要

点云为观众提供了直观的几何理解,但需要大量数据。移动图像专家组(MPEG)开发了基于视频的点云压缩技术,压缩率范围为 300-700。随着压缩率的提高,复杂性也随之增加,在实验环境中使用个人电脑压缩一帧图像需要 101.36 秒。为了实现实时点云压缩处理,本文提出的直接补丁投影(DPP)方法通过根据点的几何位置对点进行分类和投影,简化了复杂的补丁分割过程。DPP 方法将斑块分割的复杂度从每帧 25.75 秒降至 0.10 秒,整个过程比传统方法快 8.76 倍。因此,所提出的 DPP 方法以比特率开销为代价,在缩短时间(4.7-5.5 倍)的情况下获得了与传统方法相似的峰值信噪比(PSNR)结果。客观和主观结果表明,在轻量级设备环境中需要低复杂度要求时,可以考虑采用所提出的 DPP 方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Low-complexity patch projection method for efficient and lightweight point-cloud compression

Low-complexity patch projection method for efficient and lightweight point-cloud compression

The point cloud provides viewers with intuitive geometric understanding but requires a huge amount of data. Moving Picture Experts Group (MPEG) has developed video-based point-cloud compression in the range of 300–700. As the compression rate increases, the complexity increases to the extent that it takes 101.36 s to compress one frame in an experimental environment using a personal computer. To realize real-time point-cloud compression processing, the direct patch projection (DPP) method proposed herein simplifies the complex patch segmentation process by classifying and projecting points according to their geometric positions. The DPP method decreases the complexity of the patch segmentation from 25.75 s to 0.10 s per frame, and the entire process becomes 8.76 times faster than the conventional one. Consequently, this proposed DPP method yields similar peak signal-to-noise ratio (PSNR) outcomes to those of the conventional method at reduced times (4.7–5.5 times) at the cost of bitrate overhead. The objective and subjective results show that the proposed DPP method can be considered when low-complexity requirements are required in lightweight device environments.

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来源期刊
ETRI Journal
ETRI Journal 工程技术-电信学
CiteScore
4.00
自引率
7.10%
发文量
98
审稿时长
6.9 months
期刊介绍: ETRI Journal is an international, peer-reviewed multidisciplinary journal published bimonthly in English. The main focus of the journal is to provide an open forum to exchange innovative ideas and technology in the fields of information, telecommunications, and electronics. Key topics of interest include high-performance computing, big data analytics, cloud computing, multimedia technology, communication networks and services, wireless communications and mobile computing, material and component technology, as well as security. With an international editorial committee and experts from around the world as reviewers, ETRI Journal publishes high-quality research papers on the latest and best developments from the global community.
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