Single Image Super-Resolution Based on Deep Learning Features and Dictionary Model
In traditional single image super-resolution (SR) methods based on dictionary model, a large number of image features are needed to train the SR dictionary. In general, these features are extracted by artificial rules, such as pixel gray, gradient, and texture structure. But, the dictionary model tr...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2017-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8002557/ |