Systems and methods for super-resolution synthesis based on weighted results from a random forest classifier
US10685428B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 9, 2018 |
| Grant date | Jun 16, 2020 |
| Priority date | — |
| Expiry date | Jan 31, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V40/172
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods and systems which provide super-resolution synthesis based on weighted results from a random forest classifier are described. Embodiments apply a trained random forest classifier to low-resolution patches generated from the low-resolution input image to classify the low-resolution input patches. As each low-resolution patch is fed into the random forest classifier, each decision tree in the random forest classifier “votes” for a particular class for each of the low-resolution patches. Each class is associated with a projection matrix. The projection matrices output by the decision trees are combined by a weighted average to calculate an overall projection matrix corresponding to the random forest classifier output, which is used to calculate a high-resolution patch for each low-resolution patch. The high-resolution patches are combined to generate a synthesized high-resolution image corresponding to the low-resolution input image.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.