Image enhancement via iterative refinement based on machine learning models
US12165289B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 27, 2023 |
| Grant date | Dec 10, 2024 |
| Priority date | — |
| Expiry date | Jul 27, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method includes receiving, by a computing device, training data comprising a plurality of pairs of images, wherein each pair comprises an image and at least one corresponding target version of the image. The method also includes training a neural network based on the training data to predict an enhanced version of an input image, wherein the training of the neural network comprises applying a forward Gaussian diffusion process that adds Gaussian noise to the at least one corresponding target version of each of the plurality of pairs of images to enable iterative denoising of the input image, wherein the iterative denoising is based on a reverse Markov chain associated with the forward Gaussian diffusion process. The method additionally includes outputting the trained neural network.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.