Multisource Images Analysis Using Collaborative Clustering - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue EURASIP Journal on Advances in Signal Processing Année : 2008

Multisource Images Analysis Using Collaborative Clustering

Résumé

The development of very high-resolution (VHR) satellite imagery has produced a huge amount of data. The multiplication of satellites which embed different types of sensors provides a lot of heterogeneous images. Consequently, the image analyst has often many different images available, representing the same area of the Earth surface. These images can be from different dates, produced by different sensors, or even at different resolutions. The lack of machine learning tools using all these representations in an overall process constraints to a sequential analysis of these various images. In order to use all the information available simultaneously, we propose a framework where different algorithms can use different views of the scene. Each one works on a different remotely sensed image and, thus, produces different and useful information. These algorithms work together in a collaborative way through an automatic and mutual refinement of their results, so that all the results have almost the same number of clusters, which are statistically similar. Finally, a unique result is produced, representing a consensus among the information obtained by each clustering method on its own image. The unified result and the complementarity of the single results (i.e., the agreement between the clustering methods as well as the disagreement) lead to a better understanding of the scene. The experiments carried out on multispectral remote sensing images have shown that this method is efficient to extract relevant information and to improve the scene understanding.
Fichier principal
Vignette du fichier
eurasip2008.pdf (8.31 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01878610 , version 1 (21-09-2018)

Identifiants

Citer

Germain Forestier, Cédric Wemmert, Pierre Gancarski. Multisource Images Analysis Using Collaborative Clustering. EURASIP Journal on Advances in Signal Processing, 2008, 2008 (1), ⟨10.1155/2008/374095⟩. ⟨hal-01878610⟩
24 Consultations
30 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More