Efficient use of quantization parameters in machine-learning models for video coding
US10674152B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 18, 2018 |
| Grant date | Jun 2, 2020 |
| Priority date | — |
| Expiry date | Sep 18, 2038 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04N19/96
- WIPO fieldAudio-visual technology
- WIPO sectorElectrical engineering
Abstract
A method for encoding an image block includes presenting, to a machine-learning model, the image block and a first value corresponding to a first quantization parameter; obtaining first mode decision parameters from the machine-learning model; and encoding the image block using the first mode decision parameters. The first value results from a non-linear function using the first quantization parameter as input. The machine-learning model is trained to output mode decision parameters by using training data. Each training datum includes a training block that is encoded by a second encoder, second mode decision parameters used by the second encoder for encoding the training block, and a second value corresponding to a second quantization parameter. The second encoder used the second quantization parameter for encoding the training block and the second value results from the non-linear function using the second quantization parameter as input.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.