Automated process for dynamic material classification in remotely sensed imagery
US11250260B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 15, 2019 |
| Grant date | Feb 15, 2022 |
| Priority date | — |
| Expiry date | Feb 19, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V20/194
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An automated system is provided for classifying materials in remotely-sensed imagery based on automated construction of a dynamic classifier—namely, a classifier that is automatically trained on the same image to which it is then subsequently applied. A first automated process identifies high confidence exemplars of each class using tailored classification techniques. This data is then used to train a supervised classification model (e.g., discriminant analysis), and the resultant classifier is applied to other pixels in the image that are unclassified or uncertain. Dynamic classification is automatically customized to the current image and can yield a more accurate and efficient material classification versus a static (image-independent) or manually trained classifier. It can overcome various confounding factors including inconsistencies in radiometric calibration, atmospheric conditions, and atmospheric distortions of ground spectra; different viewing and illumination geometries; and regional variations in the composition of certain materials like asphalt and concrete.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.