Reconstruction algorithm based on multi-reference frames hypothesis optimization for compressive sensing
In multi-hypothesis based distributed compressed video sensing systems,the quality of the multi-hypothesis set has important influence on the reconstruction performance of decoder.However,the acquiring of the hypothesis set has not been concerned in existing works.A reconstruction algorithm based on...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2017-12-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2017297/ |
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| _version_ | 1841539507806011392 |
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| author | Yong-hong KUO Ru-quan WANG Jian CHEN |
| author_facet | Yong-hong KUO Ru-quan WANG Jian CHEN |
| author_sort | Yong-hong KUO |
| collection | DOAJ |
| description | In multi-hypothesis based distributed compressed video sensing systems,the quality of the multi-hypothesis set has important influence on the reconstruction performance of decoder.However,the acquiring of the hypothesis set has not been concerned in existing works.A reconstruction algorithm based on multi-reference frames hypothesis optimization (MRHO) was proposed.This algorithm expanded the selection of hypothesis vectors by increasing the number of reference frames.The quality of the prediction set was improved by hypotheses optimization selection under the same size with the original hypothesis set.Simulation results show that the proposed MRHO algorithm effectively improves the reconstructed quality of the distributed compressed video sensing scheme. |
| format | Article |
| id | doaj-art-634d0716d8f6419289cfad79171d1303 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2017-12-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-634d0716d8f6419289cfad79171d13032025-01-14T07:13:26ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2017-12-01381959713774Reconstruction algorithm based on multi-reference frames hypothesis optimization for compressive sensingYong-hong KUORu-quan WANGJian CHENIn multi-hypothesis based distributed compressed video sensing systems,the quality of the multi-hypothesis set has important influence on the reconstruction performance of decoder.However,the acquiring of the hypothesis set has not been concerned in existing works.A reconstruction algorithm based on multi-reference frames hypothesis optimization (MRHO) was proposed.This algorithm expanded the selection of hypothesis vectors by increasing the number of reference frames.The quality of the prediction set was improved by hypotheses optimization selection under the same size with the original hypothesis set.Simulation results show that the proposed MRHO algorithm effectively improves the reconstructed quality of the distributed compressed video sensing scheme.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2017297/compressed sensingdistributed compressive video sensingmulti-hypothesis set optimizationmulti-reference frames selection |
| spellingShingle | Yong-hong KUO Ru-quan WANG Jian CHEN Reconstruction algorithm based on multi-reference frames hypothesis optimization for compressive sensing Tongxin xuebao compressed sensing distributed compressive video sensing multi-hypothesis set optimization multi-reference frames selection |
| title | Reconstruction algorithm based on multi-reference frames hypothesis optimization for compressive sensing |
| title_full | Reconstruction algorithm based on multi-reference frames hypothesis optimization for compressive sensing |
| title_fullStr | Reconstruction algorithm based on multi-reference frames hypothesis optimization for compressive sensing |
| title_full_unstemmed | Reconstruction algorithm based on multi-reference frames hypothesis optimization for compressive sensing |
| title_short | Reconstruction algorithm based on multi-reference frames hypothesis optimization for compressive sensing |
| title_sort | reconstruction algorithm based on multi reference frames hypothesis optimization for compressive sensing |
| topic | compressed sensing distributed compressive video sensing multi-hypothesis set optimization multi-reference frames selection |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2017297/ |
| work_keys_str_mv | AT yonghongkuo reconstructionalgorithmbasedonmultireferenceframeshypothesisoptimizationforcompressivesensing AT ruquanwang reconstructionalgorithmbasedonmultireferenceframeshypothesisoptimizationforcompressivesensing AT jianchen reconstructionalgorithmbasedonmultireferenceframeshypothesisoptimizationforcompressivesensing |