Fusion network-based method for image super-resolution and non-uniform motion deblurring
US11928792B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 15, 2021 |
| Grant date | Mar 12, 2024 |
| Priority date | — |
| Expiry date | Apr 11, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20221
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Disclosed is a fusion network-based method for image super-resolution and non-uniform motion deblurring. The method achieves, for the first time, restoration of a low-resolution non-uniform motion-blurred image based on a deep neural network. The network uses two branch modules to respectively extract features for image super-resolution and non-uniform motion deblurring, and achieves, by means of a feature fusion module that is trainable, adaptive fusion of outputs of the two branch modules for extracting features. Finally, an upsampling reconstruction module achieves a non-uniform motion deblurring and super-resolution task. According to the method, a self-generated set of training data is configured to perform offline training on a network, thereby achieving restoration of the low-resolution non-uniform motion-blurred image.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.