Image denoising method and apparatus based on wavelet high-frequency channel synthesis
US12045961B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 19, 2023 |
| Grant date | Jul 23, 2024 |
| Priority date | — |
| Expiry date | Oct 19, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Disclosed is an image denoising method and apparatus based on wavelet high-frequency channel synthesis. Image data are expanded to a plurality of frequency-domain channels, a plurality of “less-noise” channels and a plurality of “more-noise” channels are grouped through a noise-sort algorithm, and a denoising submodule and a synthesis submodule based on style transfer are combined to form a generative network. A discriminative network is established to add a constraint to the global loss function. After iteratively training the GAN model described above, the denoised image data can be obtained through wavelet inverse transformation. The disclosed algorithm can effectively solve the problem of “blurring” and “loss of details” introduced by traditional filtering or CNN-based deep learning methods, which is especially suitable for noise-overwhelmed image data or high dimensional image data.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.