Hyperspectral image classification method based on context-rich networks
US11941865B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 20, 2023 |
| Grant date | Mar 26, 2024 |
| Priority date | — |
| Expiry date | Jun 20, 2043 |
Classification
- Technology area (CPC Y)Emerging Cross-Sectional Technologies
- CPC primaryY02A40/10
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Disclosed in the present invention is hyperspectral image classification method based on context-rich networks. The method comprises a training stage and a prediction stage, wherein the training stage comprises image pre-processing, sample selection and network training. Firstly, performing normalization on a hyperspectral image, and then randomly selecting an appropriate proportion of marked samples from each category to generate a label map, and performing training by using the designed network; in the prediction stage, directly inputting the whole image into the trained network and obtaining a final classification result. By means of the present invention, data pre-processing, feature extraction, the process of context-rich information capturing, and classification are taken into comprehensive consideration in the whole flow; and the classification of a hyperspectral image is realized by means of constructing an end-to-end network.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.