Method of and system for customized image denoising with model interpretations
US11790492B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 17, 2020 |
| Grant date | Oct 17, 2023 |
| Priority date | — |
| Expiry date | Dec 1, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30168
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
There is provided a method and a system for customized image denoising with interpretability. A deep neural network (NN) is trained to denoise an image on a training dataset including pairs of noisy and corresponding clean images acquired from an imaging apparatus, where during the training a structured covariance score (SCS) indicative of a performance of the deep NN in recovering content of corresponding clean images relative to the denoised image is determined based on sparse conditional correlations. A test noisy image is received and denoised by the deep NN. A user feedback score indicative of user satisfaction of the denoising is obtained. A quality parameter is obtained based on the SCS and a quality metric indicative of denoised image quality is obtained from a pretrained NN, and compared with the user feedback score. If the SCS is above the user feedback score, the deep NN is provided for denoising.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.