Skip to Main content Skip to Navigation
Journal articles

Vector attribute profiles for hyperspectral image classification

Erchan Aptoula 1 Mauro Dalla Mura 2 Sébastien Lefèvre 3
2 GIPSA-SIGMAPHY - GIPSA - Signal Images Physique
GIPSA-DIS - Département Images et Signal
3 OBELIX - Environment observation with complex imagery
UBS - Université de Bretagne Sud, IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
Abstract : Morphological attribute profiles are among the most prominent spectral-spatial pixel description methods. They are efficient, effective and highly customizable multi-scale tools based on hierarchical representations of a scalar input image. Their application to multivariate images in general, and hyperspectral images in particular, has been so far conducted using the marginal strategy, i.e. by processing each image band (eventually obtained through a dimension reduction technique) independently. In this paper, we investigate the alternative vector strategy, which consists in processing the available image bands simultaneously. The vector strategy is based on a vector ordering relation that leads to the computation of a single max-and min-tree per hyperspectral dataset, from which attribute profiles can then be computed as usual. We explore known vector ordering relations for constructing such max-trees and subsequently vector attribute profiles, and introduce a combination of marginal and vector strategies. We provide an experimental comparison of these approaches in the context of hyperspectral classification with common datasets, where the proposed approach outperforms the widely used marginal strategy.
Document type :
Journal articles
Complete list of metadatas

Cited literature [47 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-01253819
Contributor : Sébastien Lefèvre <>
Submitted on : Wednesday, November 13, 2019 - 6:05:19 PM
Last modification on : Wednesday, October 7, 2020 - 11:30:04 AM

File

tgrs2016.pdf
Files produced by the author(s)

Identifiers

Citation

Erchan Aptoula, Mauro Dalla Mura, Sébastien Lefèvre. Vector attribute profiles for hyperspectral image classification. IEEE Transactions on Geoscience and Remote Sensing, Institute of Electrical and Electronics Engineers, 2016, 54 (6), pp.3208-3220. ⟨10.1109/TGRS.2015.2513424⟩. ⟨hal-01253819⟩

Share

Metrics

Record views

1421

Files downloads

331