Image compressive sensing recovery based on weighted structure group sparse representation
Non-local similarity prior has been widely paid attention to efficiently improve image recovery quality.To fur-ther improve the recovered image quality for compressive sensing (CS),an image compressive sensing recovery method based on reweighted structure group sparse representation (WSGSR) was prop...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2017-02-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2017041/ |
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| author | Jia LI Zhi-rong GAO Cheng-yi XIONG Cheng ZHOU |
| author_facet | Jia LI Zhi-rong GAO Cheng-yi XIONG Cheng ZHOU |
| author_sort | Jia LI |
| collection | DOAJ |
| description | Non-local similarity prior has been widely paid attention to efficiently improve image recovery quality.To fur-ther improve the recovered image quality for compressive sensing (CS),an image compressive sensing recovery method based on reweighted structure group sparse representation (WSGSR) was proposed.<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML"> <msub> <mi mathvariant="script">l</mi> <mn>1</mn> </msub> </math></inline-formula>-norm of WSGSR of image non-local similar patch group was used as a regularization term to optimize reconstruction,which achieved well reserving image high-frequency detail with less loss of image low-frequency component,and thus considerably improve the recon-structed image quality.A reweighted soft thresholding shrinkage method was deduced to achieve optimization solution,in which the significant coefficient with large magnitude value was shrunk by a small threshold,while the non-significant coefficient with small magnitude value was shrunk by a relative large threshold.Experimental results comparison demon-strate the effectiveness of the proposed method. |
| format | Article |
| id | doaj-art-07777753fbb94e1ebfe10e181555a6db |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2017-02-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-07777753fbb94e1ebfe10e181555a6db2025-01-14T07:11:46ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2017-02-013819620259707678Image compressive sensing recovery based on weighted structure group sparse representationJia LIZhi-rong GAOCheng-yi XIONGCheng ZHOUNon-local similarity prior has been widely paid attention to efficiently improve image recovery quality.To fur-ther improve the recovered image quality for compressive sensing (CS),an image compressive sensing recovery method based on reweighted structure group sparse representation (WSGSR) was proposed.<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML"> <msub> <mi mathvariant="script">l</mi> <mn>1</mn> </msub> </math></inline-formula>-norm of WSGSR of image non-local similar patch group was used as a regularization term to optimize reconstruction,which achieved well reserving image high-frequency detail with less loss of image low-frequency component,and thus considerably improve the recon-structed image quality.A reweighted soft thresholding shrinkage method was deduced to achieve optimization solution,in which the significant coefficient with large magnitude value was shrunk by a small threshold,while the non-significant coefficient with small magnitude value was shrunk by a relative large threshold.Experimental results comparison demon-strate the effectiveness of the proposed method.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2017041/compressive sensingimage reconstructionweighted structure group sparse representationweighted soft thresholding shrinkage |
| spellingShingle | Jia LI Zhi-rong GAO Cheng-yi XIONG Cheng ZHOU Image compressive sensing recovery based on weighted structure group sparse representation Tongxin xuebao compressive sensing image reconstruction weighted structure group sparse representation weighted soft thresholding shrinkage |
| title | Image compressive sensing recovery based on weighted structure group sparse representation |
| title_full | Image compressive sensing recovery based on weighted structure group sparse representation |
| title_fullStr | Image compressive sensing recovery based on weighted structure group sparse representation |
| title_full_unstemmed | Image compressive sensing recovery based on weighted structure group sparse representation |
| title_short | Image compressive sensing recovery based on weighted structure group sparse representation |
| title_sort | image compressive sensing recovery based on weighted structure group sparse representation |
| topic | compressive sensing image reconstruction weighted structure group sparse representation weighted soft thresholding shrinkage |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2017041/ |
| work_keys_str_mv | AT jiali imagecompressivesensingrecoverybasedonweightedstructuregroupsparserepresentation AT zhironggao imagecompressivesensingrecoverybasedonweightedstructuregroupsparserepresentation AT chengyixiong imagecompressivesensingrecoverybasedonweightedstructuregroupsparserepresentation AT chengzhou imagecompressivesensingrecoverybasedonweightedstructuregroupsparserepresentation |