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...
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| Veröffentlicht in: | IEEE access 2019, Vol.7, p.37039-37049 |
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| creator | Lewis D., John Singhal, Vanika Majumdar, Angshul |
| 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. |
| doi_str_mv | 10.1109/ACCESS.2018.2881492 |
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| source | Electronic Journals Library; DOAJ Directory of Open Access Journals; IEEE Xplore Open Access Journals |
| subjects | deep learning Denoising Dictionaries dictionary learning Image reconstruction Inverse problems Learning Machine learning Neural networks Noise reduction reconstruction super-resolution Training Transforms |
| title | Solving Inverse Problems in Imaging via Deep Dictionary Learning |
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