Compressive Superresolution Imaging Based on Local and Nonlocal Regularizations
Compressive sensing based on a redundant dictionary has been successfully applied in superresolution imaging. However, due to the neglect of the local and nonlocal interactions of patches of a single image, the reconstructed results are not satisfactory in noise suppression and edge sharpness. In th...
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| Format: | Article |
| Language: | English |
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IEEE
2016-01-01
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| Series: | IEEE Photonics Journal |
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| Online Access: | https://ieeexplore.ieee.org/document/7377008/ |
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| author | Yicheng Sun Guohua Gu Xiubao Sui Yuan Liu |
| author_facet | Yicheng Sun Guohua Gu Xiubao Sui Yuan Liu |
| author_sort | Yicheng Sun |
| collection | DOAJ |
| description | Compressive sensing based on a redundant dictionary has been successfully applied in superresolution imaging. However, due to the neglect of the local and nonlocal interactions of patches of a single image, the reconstructed results are not satisfactory in noise suppression and edge sharpness. In this paper, we propose an improved method by adding steering kernel regression and a nonlocal means filter as two regularization terms and use an efficient clustering subdictionary learning scheme. We further demonstrate better results on true images in terms of traditional image quality assessment metrics. |
| format | Article |
| id | doaj-art-a3e471b01a614e89bce388f33a9c5a5d |
| institution | Matheson Library |
| issn | 1943-0655 |
| language | English |
| publishDate | 2016-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Photonics Journal |
| spelling | doaj-art-a3e471b01a614e89bce388f33a9c5a5d2025-07-01T23:01:52ZengIEEEIEEE Photonics Journal1943-06552016-01-018111210.1109/JPHOT.2016.25162517377008Compressive Superresolution Imaging Based on Local and Nonlocal RegularizationsYicheng Sun0Guohua Gu1Xiubao Sui2https://orcid.org/0000-0002-1638-0701Yuan Liu3Sch. of Electron. & Opt. Eng., Nanjing Univ. of Sci. & Technol., Nanjing, ChinaSch. of Electron. & Opt. Eng., Nanjing Univ. of Sci. & Technol., Nanjing, ChinaSch. of Electron. & Opt. Eng., Nanjing Univ. of Sci. & Technol., Nanjing, ChinaSch. of Electron. & Opt. Eng., Nanjing Univ. of Sci. & Technol., Nanjing, ChinaCompressive sensing based on a redundant dictionary has been successfully applied in superresolution imaging. However, due to the neglect of the local and nonlocal interactions of patches of a single image, the reconstructed results are not satisfactory in noise suppression and edge sharpness. In this paper, we propose an improved method by adding steering kernel regression and a nonlocal means filter as two regularization terms and use an efficient clustering subdictionary learning scheme. We further demonstrate better results on true images in terms of traditional image quality assessment metrics.https://ieeexplore.ieee.org/document/7377008/super-resolutioncompressive sensingnonlocal means filtersteering kernel regressionclustering sub-dictionaries |
| spellingShingle | Yicheng Sun Guohua Gu Xiubao Sui Yuan Liu Compressive Superresolution Imaging Based on Local and Nonlocal Regularizations IEEE Photonics Journal super-resolution compressive sensing nonlocal means filter steering kernel regression clustering sub-dictionaries |
| title | Compressive Superresolution Imaging Based on Local and Nonlocal Regularizations |
| title_full | Compressive Superresolution Imaging Based on Local and Nonlocal Regularizations |
| title_fullStr | Compressive Superresolution Imaging Based on Local and Nonlocal Regularizations |
| title_full_unstemmed | Compressive Superresolution Imaging Based on Local and Nonlocal Regularizations |
| title_short | Compressive Superresolution Imaging Based on Local and Nonlocal Regularizations |
| title_sort | compressive superresolution imaging based on local and nonlocal regularizations |
| topic | super-resolution compressive sensing nonlocal means filter steering kernel regression clustering sub-dictionaries |
| url | https://ieeexplore.ieee.org/document/7377008/ |
| work_keys_str_mv | AT yichengsun compressivesuperresolutionimagingbasedonlocalandnonlocalregularizations AT guohuagu compressivesuperresolutionimagingbasedonlocalandnonlocalregularizations AT xiubaosui compressivesuperresolutionimagingbasedonlocalandnonlocalregularizations AT yuanliu compressivesuperresolutionimagingbasedonlocalandnonlocalregularizations |