Feature-monitored shape unifying for lossy SPM-JBIG2

Y. Ye, P. Cosman
{"title":"Feature-monitored shape unifying for lossy SPM-JBIG2","authors":"Y. Ye, P. Cosman","doi":"10.1109/ISSPA.2001.950171","DOIUrl":null,"url":null,"abstract":"Shape unifying is a very efficient preprocessing technique used in lossy SPM-JBIG2 systems. It permits isolated errors between the current bitmap and its reference to improve refinement coding efficiency. Compared to lossless coding, it can improve compression by about 32% while causing very little visual information loss. When bigger error clusters are permitted in shape unifying, further compression gain can be achieved but at the price of more noticeable visual information loss and even character substitution errors. We propose a feature monitored shape unifying procedure that can significantly lower the risk of substitution errors when permitting bigger errors. Experiments show that, compared to the unmonitored shape unifying, the feature monitored version can suppress more than 2/3 of all substitution errors while achieving additional compression improvements of 30-40%.","PeriodicalId":236050,"journal":{"name":"Proceedings of the Sixth International Symposium on Signal Processing and its Applications (Cat.No.01EX467)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Sixth International Symposium on Signal Processing and its Applications (Cat.No.01EX467)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSPA.2001.950171","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

Abstract

Shape unifying is a very efficient preprocessing technique used in lossy SPM-JBIG2 systems. It permits isolated errors between the current bitmap and its reference to improve refinement coding efficiency. Compared to lossless coding, it can improve compression by about 32% while causing very little visual information loss. When bigger error clusters are permitted in shape unifying, further compression gain can be achieved but at the price of more noticeable visual information loss and even character substitution errors. We propose a feature monitored shape unifying procedure that can significantly lower the risk of substitution errors when permitting bigger errors. Experiments show that, compared to the unmonitored shape unifying, the feature monitored version can suppress more than 2/3 of all substitution errors while achieving additional compression improvements of 30-40%.
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
有损SPM-JBIG2的特征监测形状统一
形状统一是一种用于有损SPM-JBIG2系统的高效预处理技术。它允许当前位图与其引用之间的孤立错误,以提高改进编码效率。与无损编码相比,它可以提高约32%的压缩,同时造成很少的视觉信息损失。当形状统一中允许更大的错误簇时,可以获得进一步的压缩增益,但代价是更明显的视觉信息丢失甚至字符替换错误。我们提出了一种特征监控形状统一过程,可以在允许较大误差的情况下显著降低替换错误的风险。实验表明,与不受监控的形状统一相比,特征监控版本可以抑制超过2/3的替换错误,同时实现30-40%的额外压缩改进。
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
Large dynamic range time-frequency signal analysis with application to helicopter Doppler radar data Statistical analysis of neural network modeling and identification of nonlinear systems with memory Design of oversampled uniform DFT filter banks with reduced inband aliasing and delay constraints Identification of DCT signs for sub-block coding Skin color detection for face localization in human-machine communications
×
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