37-ACRS_H_1.pdf
This paper describes different approaches in feature extraction for a hyperspectral image classification. For the actual feature extraction, principal components transformation, band correlation method, average intensity of the visible/infrared ranges and spectral knowledge are used. The output of each of the feature extraction method is used for a classification process. The results are analyzed and compared.
Additional Information
| Field | Value |
|---|---|
| Data last updated | January 29, 2020 |
| Metadata last updated | January 29, 2020 |
| Created | January 29, 2020 |
| Format | application/pdf |
| License | Creative Commons Attribution |
| created | over 5 years ago |
| format | |
| has views | True |
| id | ed19b458-39bb-47f5-af3d-30e2258d02c6 |
| last modified | over 5 years ago |
| mimetype | application/pdf |
| on same domain | True |
| package id | 4e677c91-326b-4dd4-979c-8020ebf07689 |
| revision id | dd9da000-10f9-4667-9ed4-52a036a2252f |
| size | 148.9 KiB |
| state | active |
| url type | upload |