Encoders for improved image dithering
US11790564B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 30, 2020 |
| Grant date | Oct 17, 2023 |
| Priority date | — |
| Expiry date | Aug 28, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20212
- WIPO fieldAudio-visual technology
- WIPO sectorElectrical engineering
Abstract
Example embodiments allow for training of encoders (e.g., artificial neural networks (ANNs)) to facilitate dithering of images that have been subject to quantization in order to reduce the number of colors and/or size of the images. Such a trained encoder generates a dithering image from an input quantized image that can be combined, by addition or by some other process, with the quantized image to result in a dithered output image that exhibits reduced banding or is otherwise aesthetically improved relative to the un-dithered quantized image. The use of a trained encoder to facilitate dithering of quantized images allows the dithering to be performed in a known period of time using a known amount of memory, in contrast to alternative iterative dithering methods. Additionally, the trained encoder can be differentiable, allowing it to be part of a deep learning image processing pipeline or other machine learning pipeline.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.