Method and system for extracting and classifying features of hyperspectral remote sensing image
US10509984B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 13, 2018 |
| Grant date | Dec 17, 2019 |
| Priority date | — |
| Expiry date | Jun 27, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V10/467
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present invention provides a method for extracting and classifying features of hyperspectral remote sensing image, including: an sampling step, a binarizing step, a coding step, a statistical calculating step, a concatenating step, and a classifying step. The present invention further provides a system for extracting and classifying features of hyperspectral remote sensing image. The technical solution provided by the present invention can make full use of the contextual relationship between the spectral domain and the spatial domain in a hyperspectral remote sensing image by extending two-dimensional LBPs into three-dimensional LBPs, and has good robustness to noise by introducing a relaxation threshold discrimination operation. Furthermore, the rotation-invariant three-dimensional LBP model provided by the present invention takes account of the essential characteristics of the hyperspectral remote sensing image, and therefore the present solution has advantages that it is targeted, simple in operation and high in calculation efficiency.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.