基于小波的自适应嵌入分形图像编码

A. Abdelwahab, H. Elmogazy
{"title":"基于小波的自适应嵌入分形图像编码","authors":"A. Abdelwahab, H. Elmogazy","doi":"10.1109/ICCES.2006.320448","DOIUrl":null,"url":null,"abstract":"An embedded fractal coding scheme for low bit rate transmission of discrete wavelet transform coefficients is proposed in this paper. Using 3-level 2D discrete wavelet transform (2D-DWT) for image data compression, fractal encoding is employed for generating the fractal parameters of the DWT coefficients of the third level subimages (the coarser scale). This should decrease the encoding fractal processing time. The subimages of the third level and that of the subsequent levels (finer scales) are reconstructed from the transmitted fractal parameters of level three by exploiting the high correlations among the DWT coefficients in different scales which is called embedded fractal coding (EFC) scheme. For further reconstructed image quality improvement, an adaptive technique using vector quantization is used to transmit some DWT coefficients. This is called the adaptive embedded fractal coding/vector quantization (AEFC/VQ) scheme. Experimental results showed that the proposed scheme can provide, with low processing time, good image quality in terms of peak signal to noise ratio (PSNR) at low bit rate","PeriodicalId":261853,"journal":{"name":"2006 International Conference on Computer Engineering and Systems","volume":"258 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Wavelet-Based Adaptive Embedded Fractal Image Coding\",\"authors\":\"A. Abdelwahab, H. Elmogazy\",\"doi\":\"10.1109/ICCES.2006.320448\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An embedded fractal coding scheme for low bit rate transmission of discrete wavelet transform coefficients is proposed in this paper. Using 3-level 2D discrete wavelet transform (2D-DWT) for image data compression, fractal encoding is employed for generating the fractal parameters of the DWT coefficients of the third level subimages (the coarser scale). This should decrease the encoding fractal processing time. The subimages of the third level and that of the subsequent levels (finer scales) are reconstructed from the transmitted fractal parameters of level three by exploiting the high correlations among the DWT coefficients in different scales which is called embedded fractal coding (EFC) scheme. For further reconstructed image quality improvement, an adaptive technique using vector quantization is used to transmit some DWT coefficients. This is called the adaptive embedded fractal coding/vector quantization (AEFC/VQ) scheme. Experimental results showed that the proposed scheme can provide, with low processing time, good image quality in terms of peak signal to noise ratio (PSNR) at low bit rate\",\"PeriodicalId\":261853,\"journal\":{\"name\":\"2006 International Conference on Computer Engineering and Systems\",\"volume\":\"258 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 International Conference on Computer Engineering and Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCES.2006.320448\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 International Conference on Computer Engineering and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCES.2006.320448","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

提出了一种用于离散小波变换系数低比特率传输的嵌入式分形编码方案。利用3级二维离散小波变换(2D-DWT)对图像数据进行压缩,采用分形编码生成第三级子图像(粗尺度)的DWT系数的分形参数。这将减少编码分形处理时间。利用传输的第三层分形参数在不同尺度下DWT系数之间的高度相关性,重构出第三层和后续更细尺度的子图像,称为嵌入分形编码(EFC)方案。为了进一步提高重建图像的质量,采用矢量量化自适应技术传输一些DWT系数。这被称为自适应嵌入分形编码/矢量量化(AEFC/VQ)方案。实验结果表明,在低比特率下,该方案可以在较短的处理时间内提供较好的峰值信噪比图像质量
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Wavelet-Based Adaptive Embedded Fractal Image Coding
An embedded fractal coding scheme for low bit rate transmission of discrete wavelet transform coefficients is proposed in this paper. Using 3-level 2D discrete wavelet transform (2D-DWT) for image data compression, fractal encoding is employed for generating the fractal parameters of the DWT coefficients of the third level subimages (the coarser scale). This should decrease the encoding fractal processing time. The subimages of the third level and that of the subsequent levels (finer scales) are reconstructed from the transmitted fractal parameters of level three by exploiting the high correlations among the DWT coefficients in different scales which is called embedded fractal coding (EFC) scheme. For further reconstructed image quality improvement, an adaptive technique using vector quantization is used to transmit some DWT coefficients. This is called the adaptive embedded fractal coding/vector quantization (AEFC/VQ) scheme. Experimental results showed that the proposed scheme can provide, with low processing time, good image quality in terms of peak signal to noise ratio (PSNR) at low bit rate
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