Improved Image Compression Using Backpropagation Networks

G. Qiu, T. Terrell, M. Varley
{"title":"Improved Image Compression Using Backpropagation Networks","authors":"G. Qiu, T. Terrell, M. Varley","doi":"10.1109/NNAT.1993.586056","DOIUrl":null,"url":null,"abstract":"This paper describes an improved image compression scheme using backpropagation networks. The new scheme is aimed at improving the networks' generalisation capabilities, thereby enabling them to effectively compress a wide range of novel images. The networks operate, and are trained on, residual image blocks, thus eliminating the problem of varying average image intensities highlighted by Cottrell et al. Tabulated experimental results and example reconstructed novel images, for the method of [3] and the new technique, are presented, which demonstrate the improved image compression performance gained using this new technique. 131.","PeriodicalId":164805,"journal":{"name":"Workshop on Neural Network Applications and Tools","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1993-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Workshop on Neural Network Applications and Tools","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NNAT.1993.586056","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 19

Abstract

This paper describes an improved image compression scheme using backpropagation networks. The new scheme is aimed at improving the networks' generalisation capabilities, thereby enabling them to effectively compress a wide range of novel images. The networks operate, and are trained on, residual image blocks, thus eliminating the problem of varying average image intensities highlighted by Cottrell et al. Tabulated experimental results and example reconstructed novel images, for the method of [3] and the new technique, are presented, which demonstrate the improved image compression performance gained using this new technique. 131.
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
利用反向传播网络改进图像压缩
本文介绍了一种利用反向传播网络改进的图像压缩方案。新方案旨在提高网络的泛化能力,从而使它们能够有效地压缩大范围的新图像。该网络在残差图像块上运行和训练,从而消除了Cottrell等人强调的平均图像强度变化的问题。本文给出了[3]方法和新技术的实验结果和重建新图像的实例,证明了使用该新技术获得的图像压缩性能的提高。131.
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Using Kohonen Feature Maps To Monitor The Condition Of Synchronous Generators Improved Image Compression Using Backpropagation Networks A Neural Network Quality Classifier For Tig Welding Without Filler Intelligent Gain Scheduling (igs) Using Neural Networks For Robotic Manipulators Prototype Of A Neuro-fuzzy Controlled Model Lorry
×
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