|
Depot Institutionnel de l'UMBB >
Publications Scientifiques >
Communications Internationales >
Veuillez utiliser cette adresse pour citer ce document :
http://dlibrary.univ-boumerdes.dz:8080/handle/123456789/6169
|
| Titre: | An Object-Based Approach to VHR Image Classification |
| Auteur(s): | S.B., Asma
D., Abdelhamid |
| Mots-clés: | Image Classification
Object-Based
Remote Sensing
Superpixels |
| Date de publication: | 2020 |
| Editeur: | Institute of Electrical and Electronics Engineers |
| Collection/Numéro: | 2020 Mediterranean and Middle-East Geoscience and Remote Sensing Symposium, M2GARSS 2020 - Proceedings; |
| Résumé: | This paper introduces a novel method for the classification of very high resolution, multispectral, remote sensing images. We combine the advantages of both pixel-based and object-based classification techniques. First, the pixels contained in the image are grouped into different batches, called segments, using the algorithm of superpixels. Then the superpixels are merged into more significant objects using one distance metrics among a variety. Finally, the resulting image is classified by the Support Vector Machines classifier. The performance of the proposed approach is compared to the classical spectral-based classification. Using overall accuracy and average accuracy, the results obtained on a high resolution multispectral Boumerdes image reveal the efficiency of the proposed method |
| URI/URL: | https://www.scopus.com/record/display.uri?eid=2-s2.0-85086715489&origin=SingleRecordEmailAlert&dgcid=raven_sc_affil_en_us_email&txGid=cc2c6ecdf7c879938a36b62b38e690c2
http://dlibrary.univ-boumerdes.dz:8080/handle/123456789/6169 |
| ISBN: | 978-172812190-1 |
| Collection(s) : | Communications Internationales
|
Fichier(s) constituant ce document :
|
Tous les documents dans DSpace sont protégés par copyright, avec tous droits réservés.
|
