Extended attribute profiles and extended multi-attribute profiles are presented for the analysis of hyperspectral high-resolution images. These extended profiles are based on morphological attribute filters and, through a multi-level analysis, are capable of extracting spatial features that can better model the spatial information, with respect to conventional extended morphological profiles. The features extracted by the proposed extended profiles were considered for a classification task. Two hyperspectral high-resolution datasets acquired for the city of Pavia, Italy, were considered in the analysis. The effectiveness of the introduced operators in modelling the spatial information was proved by the higher classification accuracies obtained with respect to those achieved by a conventional extended morphological profile. © 2010 Taylor & Francis.

Extended Profiles with Morphological Attribute Filters for the Analysis of Hyperspectral Data

Dalla Mura, Mauro;Benediktsson, Jon Atli;Bruzzone, Lorenzo
2010-01-01

Abstract

Extended attribute profiles and extended multi-attribute profiles are presented for the analysis of hyperspectral high-resolution images. These extended profiles are based on morphological attribute filters and, through a multi-level analysis, are capable of extracting spatial features that can better model the spatial information, with respect to conventional extended morphological profiles. The features extracted by the proposed extended profiles were considered for a classification task. Two hyperspectral high-resolution datasets acquired for the city of Pavia, Italy, were considered in the analysis. The effectiveness of the introduced operators in modelling the spatial information was proved by the higher classification accuracies obtained with respect to those achieved by a conventional extended morphological profile. © 2010 Taylor & Francis.
2010
22
Dalla Mura, Mauro; Benediktsson, Jon Atli; B., Waske; Bruzzone, Lorenzo
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/85225
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 378
  • ???jsp.display-item.citation.isi??? 341
  • OpenAlex ND
social impact