复合图像压缩的自适应分辨率矢量量化技术及基本码本设计方法

T. Nakayama, M. Konda, K. Takeuchi, K. Kotani, T. Ohmi
{"title":"复合图像压缩的自适应分辨率矢量量化技术及基本码本设计方法","authors":"T. Nakayama, M. Konda, K. Takeuchi, K. Kotani, T. Ohmi","doi":"10.1109/ICME.2003.1221675","DOIUrl":null,"url":null,"abstract":"In order to increase the performance of image compression by vector quantization (VQ), we propose a systematic codebook design method without using learning sequences for 4/spl times/4 and 2/spl times/2 pixel blocks. According to the method, the codebook can be applied to all kinds of images and exhibits equivalent compression performance to the specific codebooks created individually by conventional learning method using corresponding images. Furthermore, we have developed a novel VQ-based image-coding algorithm suitable for compound images. Adaptive resolution VQ (AR-VQ) method, which is composed of three key techniques, i.e., the edge detection, the resolution conversion, and the entropy coding, can realize much superior compression performance than the JPEG and the JPEG-2000. On the compression of the XGA (1024/spl times/768 pixels) images including text, for instance, there exist an overwhelming performance difference of 5 to 40 dB in compressed image quality.","PeriodicalId":118560,"journal":{"name":"2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Adaptive resolution vector quantization technique and basic codebook design method for compound image compression\",\"authors\":\"T. Nakayama, M. Konda, K. Takeuchi, K. Kotani, T. Ohmi\",\"doi\":\"10.1109/ICME.2003.1221675\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to increase the performance of image compression by vector quantization (VQ), we propose a systematic codebook design method without using learning sequences for 4/spl times/4 and 2/spl times/2 pixel blocks. According to the method, the codebook can be applied to all kinds of images and exhibits equivalent compression performance to the specific codebooks created individually by conventional learning method using corresponding images. Furthermore, we have developed a novel VQ-based image-coding algorithm suitable for compound images. Adaptive resolution VQ (AR-VQ) method, which is composed of three key techniques, i.e., the edge detection, the resolution conversion, and the entropy coding, can realize much superior compression performance than the JPEG and the JPEG-2000. On the compression of the XGA (1024/spl times/768 pixels) images including text, for instance, there exist an overwhelming performance difference of 5 to 40 dB in compressed image quality.\",\"PeriodicalId\":118560,\"journal\":{\"name\":\"2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698)\",\"volume\":\"37 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-07-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICME.2003.1221675\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICME.2003.1221675","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

为了提高矢量量化(VQ)图像压缩性能,提出了一种不使用4/spl次/4和2/spl次/2像素块学习序列的系统码本设计方法。根据该方法,该码本可以应用于各种图像,并且具有与传统学习方法使用相应图像单独创建的特定码本相当的压缩性能。此外,我们还开发了一种新的适合于复合图像的基于vq的图像编码算法。自适应分辨率VQ (AR-VQ)方法由边缘检测、分辨率转换和熵编码三个关键技术组成,可以实现比JPEG和JPEG-2000优越得多的压缩性能。例如,在压缩包括文本在内的XGA (1024/spl倍/768像素)图像时,压缩图像质量存在5到40 dB的压倒性性能差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptive resolution vector quantization technique and basic codebook design method for compound image compression
In order to increase the performance of image compression by vector quantization (VQ), we propose a systematic codebook design method without using learning sequences for 4/spl times/4 and 2/spl times/2 pixel blocks. According to the method, the codebook can be applied to all kinds of images and exhibits equivalent compression performance to the specific codebooks created individually by conventional learning method using corresponding images. Furthermore, we have developed a novel VQ-based image-coding algorithm suitable for compound images. Adaptive resolution VQ (AR-VQ) method, which is composed of three key techniques, i.e., the edge detection, the resolution conversion, and the entropy coding, can realize much superior compression performance than the JPEG and the JPEG-2000. On the compression of the XGA (1024/spl times/768 pixels) images including text, for instance, there exist an overwhelming performance difference of 5 to 40 dB in compressed image quality.
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
×
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