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 |
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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 4 years ago |
format | |
has views | True |
id | ed19b458-39bb-47f5-af3d-30e2258d02c6 |
last modified | over 4 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 |