High Compression Rate Architecture For Texture Padding Based on V-PCC

Cheng-Lin Lu, He-Sheng Chou, Yabo Huang, Mei-Ling Chan, Szu-Yin Lin, Shih-Lun Chen
{"title":"High Compression Rate Architecture For Texture Padding Based on V-PCC","authors":"Cheng-Lin Lu, He-Sheng Chou, Yabo Huang, Mei-Ling Chan, Szu-Yin Lin, Shih-Lun Chen","doi":"10.1109/ICCE-Taiwan58799.2023.10227018","DOIUrl":null,"url":null,"abstract":"Video-based point cloud compression(V-PCC)is a point cloud compression standard formulated by the Moving Picture Experts Group(MPEG) organization. The concept of this standard is to project 3D point cloud information onto a 2D plane and generate 2D image, namely geometry map, texture map, and occupancy map. Overlap 2D images to form 3D depth from three images, combine color and position information, and then encode and decode using High Efficiency Video Coding (HEVC) compression. However, the projected image will have obvious holes. These holes are regarded as high-frequency signal in the image, which will have a bad impact on the subsequent compression rate. It is necessary to use image filling to smooth the image, reduce high-frequency signal, and facilitate subsequent compression processing. Therefore, the purpose of this research is to develop a series of anti-noise procedures to fill and smooth images with High-Efficiency Video Coding(HEVC), including mean filter, Smooth Pull Push Algorithm(SPP), etc. This algorithm has been implemented in mpeg-pcc-tmc2-release-v8.0 [1], and the obtained data proves that although PSNR needs to be sacrificed, it can effectively reduce the number of compressed bytes after texture map filling.","PeriodicalId":112903,"journal":{"name":"2023 International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCE-Taiwan58799.2023.10227018","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Video-based point cloud compression(V-PCC)is a point cloud compression standard formulated by the Moving Picture Experts Group(MPEG) organization. The concept of this standard is to project 3D point cloud information onto a 2D plane and generate 2D image, namely geometry map, texture map, and occupancy map. Overlap 2D images to form 3D depth from three images, combine color and position information, and then encode and decode using High Efficiency Video Coding (HEVC) compression. However, the projected image will have obvious holes. These holes are regarded as high-frequency signal in the image, which will have a bad impact on the subsequent compression rate. It is necessary to use image filling to smooth the image, reduce high-frequency signal, and facilitate subsequent compression processing. Therefore, the purpose of this research is to develop a series of anti-noise procedures to fill and smooth images with High-Efficiency Video Coding(HEVC), including mean filter, Smooth Pull Push Algorithm(SPP), etc. This algorithm has been implemented in mpeg-pcc-tmc2-release-v8.0 [1], and the obtained data proves that although PSNR needs to be sacrificed, it can effectively reduce the number of compressed bytes after texture map filling.
基于V-PCC的高压缩率纹理填充结构
基于视频的点云压缩(V-PCC)是由运动图像专家组(MPEG)组织制定的一种点云压缩标准。该标准的概念是将三维点云信息投影到二维平面上,生成二维图像,即几何图、纹理图和占用图。将三幅二维图像重叠形成三维深度,结合颜色和位置信息,然后使用HEVC (High Efficiency Video Coding)压缩进行编码解码。然而,投影图像会有明显的漏洞。这些孔洞被认为是图像中的高频信号,会对后续的压缩率产生不良影响。有必要使用图像填充来平滑图像,减少高频信号,便于后续压缩处理。因此,本研究的目的是开发一系列抗噪程序,以实现高效视频编码(High-Efficiency Video Coding, HEVC)对图像的填充和平滑,包括均值滤波(mean filter)、平滑拉推算法(smooth Pull Push Algorithm, SPP)等。该算法已在mpeg-pcc-tmc2-release-v8.0中实现[1],获得的数据证明,虽然需要牺牲PSNR,但可以有效减少纹理贴图填充后的压缩字节数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信