Shape Adaptive Texture Coding Based on Wavelet-Based Contourlet Transform

Zhenghua Shu, Guodong Liu, Zhihua Xie, Z. Ren
{"title":"Shape Adaptive Texture Coding Based on Wavelet-Based Contourlet Transform","authors":"Zhenghua Shu, Guodong Liu, Zhihua Xie, Z. Ren","doi":"10.1109/CISP-BMEI.2018.8633164","DOIUrl":null,"url":null,"abstract":"Transform coding of arbitrary shape object is one of the core technologies of MPEG-4 video coding. In this chapter, we propose a shape adaptive Wavelet-Based Contourlet Transform framework for MPEG4 texture coding. In the shape adaptive texture coding framework, Wavelet-Based Contourlet Transform is divided into two parts: the Wavelet-Based Contourlet Transform of the shape mask, and the Wavelet-Based Contourlet Transform of the object texture. In the Wavelet-Based Contourlet Transform phase, the shape coding is carried out using lazy Wavelet-Based Contourlet Transform, and the texture coding is carried out by 9/7 wavelets in the form of lifting. In the zerotree quantization stage of wavelet coefficients, three quantization methods are adopted according to different needs. The experimental results show that the Wavelet-Based Contourlet Transform texture coding based on object has similar low complexity with the texture coding, such as SADCT, and the performance is better. Moreover, the coding effect is better than that of SADCT at low bit rate.","PeriodicalId":117227,"journal":{"name":"2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISP-BMEI.2018.8633164","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

Transform coding of arbitrary shape object is one of the core technologies of MPEG-4 video coding. In this chapter, we propose a shape adaptive Wavelet-Based Contourlet Transform framework for MPEG4 texture coding. In the shape adaptive texture coding framework, Wavelet-Based Contourlet Transform is divided into two parts: the Wavelet-Based Contourlet Transform of the shape mask, and the Wavelet-Based Contourlet Transform of the object texture. In the Wavelet-Based Contourlet Transform phase, the shape coding is carried out using lazy Wavelet-Based Contourlet Transform, and the texture coding is carried out by 9/7 wavelets in the form of lifting. In the zerotree quantization stage of wavelet coefficients, three quantization methods are adopted according to different needs. The experimental results show that the Wavelet-Based Contourlet Transform texture coding based on object has similar low complexity with the texture coding, such as SADCT, and the performance is better. Moreover, the coding effect is better than that of SADCT at low bit rate.
基于小波轮廓波变换的形状自适应纹理编码
任意形状对象的变换编码是MPEG-4视频编码的核心技术之一。在本章中,我们提出了一种用于MPEG4纹理编码的形状自适应小波Contourlet变换框架。在形状自适应纹理编码框架中,基于小波的Contourlet变换分为两部分:形状蒙版的基于小波的Contourlet变换和目标纹理的基于小波的Contourlet变换。在基于小波的Contourlet变换阶段,使用lazy Wavelet-Based Contourlet变换进行形状编码,采用9/7个小波以提升的形式进行纹理编码。在小波系数的零树量化阶段,根据不同的需要,采用了三种量化方法。实验结果表明,基于对象的基于小波的Contourlet变换纹理编码与SADCT等纹理编码具有相似的低复杂度,且性能更好。在低比特率下,其编码效果优于SADCT。
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:604180095
Book学术官方微信