Remote sensing data fusion: Markov models and mathematical morphology for multisensor, multiresolution, and multiscale image classification - Archive ouverte HAL Accéder directement au contenu
Chapitre D'ouvrage Année : 2018

Remote sensing data fusion: Markov models and mathematical morphology for multisensor, multiresolution, and multiscale image classification

Résumé

Current and forthcoming sensor technologies and space missions are providing remote sensing scientists and practitioners with an increasing wealth and variety of data modalities. They encompass multisensor, multiresolution, multiscale, multitemporal, multipolarization, and multifrequency imagery. While they represent remarkable opportunities for the applications, they pose important challenges to the development of mathematical methods aimed at fusing the information conveyed by the input multisource data. In this framework, the present chapter continues the discussion of remote sensing data fusion, which was opened in the previous chapter. Here, the focus is on data fusion for image classification purposes. Both methodological issues of feature extraction and supervised classification are addressed. On both respects, the focus is on hierarchical image models rooted in graph theory. First, multilevel feature extraction is addressed through the latest advances in Mathematical Morphology and attribute profile theory with respect to component trees and trees of shapes. Then, joint supervised classification of multisensor, multiscale, multiresolution, and multitemporal imagery is formulated through hierarchical Markov random fields on quad-trees. Examples of experimental results with data from current VHR optical and SAR missions are shown and analysed.
Fichier non déposé

Dates et versions

hal-01632949 , version 1 (10-11-2017)

Identifiants

Citer

Jon Atli Benediktsson, Gabriele Cavallaro, Falco Nicola, Ihsen Hedhli, Vladimir Krylov, et al.. Remote sensing data fusion: Markov models and mathematical morphology for multisensor, multiresolution, and multiscale image classification. Mathematical Models for Remote Sensing Image Processing: Models and methods for the analysis of 2D satellite and aerial images, Springer, pp.277-323, 2018, ⟨10.1007/978-3-319-66330-2_7⟩. ⟨hal-01632949⟩
199 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More