Gabor cube feature selection-based classification method and system for hyperspectral remote sensing images
US10783371B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 15, 2018 |
| Grant date | Sep 22, 2020 |
| Priority date | — |
| Expiry date | Nov 13, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V20/194
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present invention provides a Gabor cube feature selection-based classification method for hyperspectral remote sensing images, comprising the following steps: generating three-dimensional Gabor filters according to set frequency and direction parameter values; convoluting hyperspectral remote sensing images with the three-dimensional Gabor filters to obtain three-dimensional Gabor features; selecting three-dimensional Gabor features, classification contribution degrees to various classes of which meet preset requirements, from the three-dimensional Gabor features; and classifying the hyperspectral remote sensing images by a multi-task joint sparse representation-based classification means by using the selected three-dimensional Gabor features. The present invention is based on the three-dimensional Gabor features, and the used three-dimensional Gabor features contain rich local change information of a signal and are competent in feature characterizing. Using a Fisher discriminant criterion not only makes full use of high-level semantics hidden among the features, but also eliminates redundant information and reduces the classification time complexity.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.