二维离散沃尔什小波变换图像压缩与算术编码

Sunil Malviya, N. Gupta, Vibhanshu Shirvastava
{"title":"二维离散沃尔什小波变换图像压缩与算术编码","authors":"Sunil Malviya, N. Gupta, Vibhanshu Shirvastava","doi":"10.1109/ICCCNT.2013.6726772","DOIUrl":null,"url":null,"abstract":"With the increasing demand of storage and transmission of digital images, image compression is now become an essential applications for storage and transmission. This paper proposes a new scheme for image compression using DWT (Discrete Wavelet Transform) taking into account sub-band features in the frequency domains. Method involves two steps firstly a two levels discrete wavelet transforms on selected input image. The original image is decomposed at different 8×8 blocks, after that apply 2D-Walsh-Wavelet Transform (WWT) on each 8×8 block of the low frequency sub-band. Firstly dividing each sub-band by a factor and then apply Arithmetic Coding on each sub-band independently. Transform each 8×8 block from LL2, and then divide each block 8×8 separated into; DC value and compressed by Arithmetic coding.","PeriodicalId":6330,"journal":{"name":"2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT)","volume":"155 1","pages":"1-4"},"PeriodicalIF":0.0000,"publicationDate":"2013-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"2D-discrete walsh wavelet transform for image compression with arithmetic coding\",\"authors\":\"Sunil Malviya, N. Gupta, Vibhanshu Shirvastava\",\"doi\":\"10.1109/ICCCNT.2013.6726772\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the increasing demand of storage and transmission of digital images, image compression is now become an essential applications for storage and transmission. This paper proposes a new scheme for image compression using DWT (Discrete Wavelet Transform) taking into account sub-band features in the frequency domains. Method involves two steps firstly a two levels discrete wavelet transforms on selected input image. The original image is decomposed at different 8×8 blocks, after that apply 2D-Walsh-Wavelet Transform (WWT) on each 8×8 block of the low frequency sub-band. Firstly dividing each sub-band by a factor and then apply Arithmetic Coding on each sub-band independently. Transform each 8×8 block from LL2, and then divide each block 8×8 separated into; DC value and compressed by Arithmetic coding.\",\"PeriodicalId\":6330,\"journal\":{\"name\":\"2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT)\",\"volume\":\"155 1\",\"pages\":\"1-4\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-07-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCCNT.2013.6726772\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCNT.2013.6726772","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10

摘要

随着数字图像存储和传输需求的不断增加,图像压缩已成为存储和传输的重要应用。本文提出了一种考虑频域子带特征的离散小波变换图像压缩新方案。该方法包括两个步骤,首先对选定的输入图像进行两级离散小波变换。将原始图像分解为不同的8×8块,然后对低频子带的每个8×8块进行2d - walsh -小波变换(WWT)。首先将每个子带划分为一个因子,然后对每个子带分别进行算术编码。从LL2变换每个8×8块,然后将每个块8×8分离成;用算术编码压缩直流值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
2D-discrete walsh wavelet transform for image compression with arithmetic coding
With the increasing demand of storage and transmission of digital images, image compression is now become an essential applications for storage and transmission. This paper proposes a new scheme for image compression using DWT (Discrete Wavelet Transform) taking into account sub-band features in the frequency domains. Method involves two steps firstly a two levels discrete wavelet transforms on selected input image. The original image is decomposed at different 8×8 blocks, after that apply 2D-Walsh-Wavelet Transform (WWT) on each 8×8 block of the low frequency sub-band. Firstly dividing each sub-band by a factor and then apply Arithmetic Coding on each sub-band independently. Transform each 8×8 block from LL2, and then divide each block 8×8 separated into; DC value and compressed by Arithmetic coding.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
“Multi-tenant SaaS cloud” Reduced order linear functional observers for large scale linear discrete-time control systems Multi pattern matching technique on fragmented and out-of-order packet streams for intrusion detection system Detection and tracking of moving objects by fuzzy textures Evacuation map generation using maze routing
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1