基于非下采样contourlet变换的压缩感知图像处理

Fu Liu, Caiyun Huang
{"title":"基于非下采样contourlet变换的压缩感知图像处理","authors":"Fu Liu, Caiyun Huang","doi":"10.1109/ICSAI.2012.6223362","DOIUrl":null,"url":null,"abstract":"A compressed sensing algorithm based on nonsubsampled contourlet transform (NSCT) is proposed, NSCT can provide better sparsity than wavelet transform does in image transform. low-frequency coefficients of the image are preserved, only high-frequency coefficients are measured. In the reconstruction, OMP algorithm is used to recover high-frequency coefficients and the image is reconstructed by inverse nonsubsampled contourlet transform. Compared with wavelet compressed sensing algorithms, simulation results demonstrate that the quality of reconstructed image can be greatly improved under the same measurement number.","PeriodicalId":90521,"journal":{"name":"IEEE International Conference on Systems Biology : [proceedings]. IEEE International Conference on Systems Biology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2012-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Compressed sensing image processing based on nonsubsampled contourlet transform\",\"authors\":\"Fu Liu, Caiyun Huang\",\"doi\":\"10.1109/ICSAI.2012.6223362\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A compressed sensing algorithm based on nonsubsampled contourlet transform (NSCT) is proposed, NSCT can provide better sparsity than wavelet transform does in image transform. low-frequency coefficients of the image are preserved, only high-frequency coefficients are measured. In the reconstruction, OMP algorithm is used to recover high-frequency coefficients and the image is reconstructed by inverse nonsubsampled contourlet transform. Compared with wavelet compressed sensing algorithms, simulation results demonstrate that the quality of reconstructed image can be greatly improved under the same measurement number.\",\"PeriodicalId\":90521,\"journal\":{\"name\":\"IEEE International Conference on Systems Biology : [proceedings]. IEEE International Conference on Systems Biology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-05-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE International Conference on Systems Biology : [proceedings]. IEEE International Conference on Systems Biology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSAI.2012.6223362\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE International Conference on Systems Biology : [proceedings]. IEEE International Conference on Systems Biology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSAI.2012.6223362","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

提出了一种基于非下采样轮廓波变换(NSCT)的压缩感知算法,NSCT在图像变换中具有比小波变换更好的稀疏性。保留图像的低频系数,只测量高频系数。在重建过程中,采用OMP算法恢复高频系数,并采用非下采样contourlet逆变换重建图像。仿真结果表明,与小波压缩感知算法相比,在相同的测量次数下,重构图像的质量有很大提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Compressed sensing image processing based on nonsubsampled contourlet transform
A compressed sensing algorithm based on nonsubsampled contourlet transform (NSCT) is proposed, NSCT can provide better sparsity than wavelet transform does in image transform. low-frequency coefficients of the image are preserved, only high-frequency coefficients are measured. In the reconstruction, OMP algorithm is used to recover high-frequency coefficients and the image is reconstructed by inverse nonsubsampled contourlet transform. Compared with wavelet compressed sensing algorithms, simulation results demonstrate that the quality of reconstructed image can be greatly improved under the same measurement number.
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:481959085
Book学术官方微信