The Classification Method of Multi-spectral Remote Sensing Images Based on Self-adaptive Minimum Distance Adjustment - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2013

The Classification Method of Multi-spectral Remote Sensing Images Based on Self-adaptive Minimum Distance Adjustment

Résumé

The phenomenon of “Same Object with Different Spectra” in the issue of multi-spectral remote sensing images land use classification makes major effects on improving accuracy. The paper based on the analysis of modeling on classification problems, proposed a method based on minimum distance self-adaptive adjustment to realize the split of cluster centers and solved the problem of identified scope intersection leading to improving the accuracy in the classifying methods difficultly. By experiments compared with the traditional methods, it can improve classification accuracy about 4% and the results prove the validity of this method.
Fichier principal
Vignette du fichier
978-3-642-36137-1_50_Chapter.pdf (4 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01348260 , version 1 (22-07-2016)

Licence

Paternité

Identifiants

Citer

Junhua Liu, Chengming Zhang, Shujing Wan. The Classification Method of Multi-spectral Remote Sensing Images Based on Self-adaptive Minimum Distance Adjustment. 6th Computer and Computing Technologies in Agriculture (CCTA), Oct 2012, Zhangjiajie, China. pp.430-437, ⟨10.1007/978-3-642-36137-1_50⟩. ⟨hal-01348260⟩
76 Consultations
69 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More