Solving Inverse Problems in Imaging via Deep Dictionary Learning
In dictionary learning-based inversion, the dictionary and coefficients are learnt adaptively from the image during the inversion process; this is a shallow approach since one layer of the dictionary is learnt. This is the first work which proposes to adaptively learn multiple layers of dictionaries...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2019-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8554065/ |
| _version_ | 1818855357480435712 |
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| author | John Lewis D. Vanika Singhal Angshul Majumdar |
| author_facet | John Lewis D. Vanika Singhal Angshul Majumdar |
| author_sort | John Lewis D. |
| collection | DOAJ |
| description | In dictionary learning-based inversion, the dictionary and coefficients are learnt adaptively from the image during the inversion process; this is a shallow approach since one layer of the dictionary is learnt. This is the first work which proposes to adaptively learn multiple layers of dictionaries during inversion. This results in our deep dictionary learning-based inversion formulation. Experiments have been carried out on denoising, super-resolution, and reconstruction. For each problem, our proposed method outperforms the state-of-the-art. |
| first_indexed | 2024-12-19T08:07:19Z |
| format | Article |
| id | doaj.art-d0a6acf986c142dc8da63ee7840ccda6 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-19T08:07:19Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-d0a6acf986c142dc8da63ee7840ccda62022-12-21T20:29:44ZengIEEEIEEE Access2169-35362019-01-017370393704910.1109/ACCESS.2018.28814928554065Solving Inverse Problems in Imaging via Deep Dictionary LearningJohn Lewis D.0Vanika Singhal1https://orcid.org/0000-0002-9773-1488Angshul Majumdar2Indraprastha Institute of Information Technology, New Delhi, IndiaIndraprastha Institute of Information Technology, New Delhi, IndiaIndraprastha Institute of Information Technology, New Delhi, IndiaIn dictionary learning-based inversion, the dictionary and coefficients are learnt adaptively from the image during the inversion process; this is a shallow approach since one layer of the dictionary is learnt. This is the first work which proposes to adaptively learn multiple layers of dictionaries during inversion. This results in our deep dictionary learning-based inversion formulation. Experiments have been carried out on denoising, super-resolution, and reconstruction. For each problem, our proposed method outperforms the state-of-the-art.https://ieeexplore.ieee.org/document/8554065/Denoisingsuper-resolutionreconstructiondictionary learningdeep learning |
| spellingShingle | John Lewis D. Vanika Singhal Angshul Majumdar Solving Inverse Problems in Imaging via Deep Dictionary Learning IEEE Access Denoising super-resolution reconstruction dictionary learning deep learning |
| title | Solving Inverse Problems in Imaging via Deep Dictionary Learning |
| title_full | Solving Inverse Problems in Imaging via Deep Dictionary Learning |
| title_fullStr | Solving Inverse Problems in Imaging via Deep Dictionary Learning |
| title_full_unstemmed | Solving Inverse Problems in Imaging via Deep Dictionary Learning |
| title_short | Solving Inverse Problems in Imaging via Deep Dictionary Learning |
| title_sort | solving inverse problems in imaging via deep dictionary learning |
| topic | Denoising super-resolution reconstruction dictionary learning deep learning |
| url | https://ieeexplore.ieee.org/document/8554065/ |
| work_keys_str_mv | AT johnlewisd solvinginverseproblemsinimagingviadeepdictionarylearning AT vanikasinghal solvinginverseproblemsinimagingviadeepdictionarylearning AT angshulmajumdar solvinginverseproblemsinimagingviadeepdictionarylearning |