Reconstruction algorithm for block compressed sensing based on variation model
The algorithms for block compressed sensing based on total variation and mixed variation (abbreviated as BCS-TV and BCS-MV) models were proposed to improve the performance of current reconstruction algorithms for the block-based compressed sensing. In the measuring phase, an image was sampled block-...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2016-01-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2016011/ |
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| _version_ | 1841539567775121408 |
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| author | Jian CHEN xiong SUKai zhi YANGXiu kui ZHENGMing qun LINLi |
| author_facet | Jian CHEN xiong SUKai zhi YANGXiu kui ZHENGMing qun LINLi |
| author_sort | Jian CHEN |
| collection | DOAJ |
| description | The algorithms for block compressed sensing based on total variation and mixed variation (abbreviated as BCS-TV and BCS-MV) models were proposed to improve the performance of current reconstruction algorithms for the block-based compressed sensing. In the measuring phase, an image was sampled block-by-block. In the recovering period, it took the sparse regularization of the natural image as a priori knowledge, and approached the target function within the whole image through the modified augmented Lagrange method and alternating direction method of multipliers (ALM-ADMM). The method proposed achieves average PSNR gain of 1.5 dB and SSIM gain of 0.05 at a more stable running speed, over the previous uniformly block-based compressed sensing. It is particularly suitable for the applications of the multimedia data processing with fixed transmission delay. |
| format | Article |
| id | doaj-art-3f50606867ce402dbaa5f8a398218f95 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2016-01-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-3f50606867ce402dbaa5f8a398218f952025-01-14T06:54:37ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2016-01-013710010959698581Reconstruction algorithm for block compressed sensing based on variation modelJian CHENxiong SUKaizhi YANGXiukui ZHENGMingqun LINLiThe algorithms for block compressed sensing based on total variation and mixed variation (abbreviated as BCS-TV and BCS-MV) models were proposed to improve the performance of current reconstruction algorithms for the block-based compressed sensing. In the measuring phase, an image was sampled block-by-block. In the recovering period, it took the sparse regularization of the natural image as a priori knowledge, and approached the target function within the whole image through the modified augmented Lagrange method and alternating direction method of multipliers (ALM-ADMM). The method proposed achieves average PSNR gain of 1.5 dB and SSIM gain of 0.05 at a more stable running speed, over the previous uniformly block-based compressed sensing. It is particularly suitable for the applications of the multimedia data processing with fixed transmission delay.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2016011/total variationimage reconstructionblock compressed sensingalternating direction method of multipliers |
| spellingShingle | Jian CHEN xiong SUKai zhi YANGXiu kui ZHENGMing qun LINLi Reconstruction algorithm for block compressed sensing based on variation model Tongxin xuebao total variation image reconstruction block compressed sensing alternating direction method of multipliers |
| title | Reconstruction algorithm for block compressed sensing based on variation model |
| title_full | Reconstruction algorithm for block compressed sensing based on variation model |
| title_fullStr | Reconstruction algorithm for block compressed sensing based on variation model |
| title_full_unstemmed | Reconstruction algorithm for block compressed sensing based on variation model |
| title_short | Reconstruction algorithm for block compressed sensing based on variation model |
| title_sort | reconstruction algorithm for block compressed sensing based on variation model |
| topic | total variation image reconstruction block compressed sensing alternating direction method of multipliers |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2016011/ |
| work_keys_str_mv | AT jianchen reconstructionalgorithmforblockcompressedsensingbasedonvariationmodel AT xiongsukai reconstructionalgorithmforblockcompressedsensingbasedonvariationmodel AT zhiyangxiu reconstructionalgorithmforblockcompressedsensingbasedonvariationmodel AT kuizhengming reconstructionalgorithmforblockcompressedsensingbasedonvariationmodel AT qunlinli reconstructionalgorithmforblockcompressedsensingbasedonvariationmodel |