Morphological attribute profiles (APs) are among the most effective methods to model the spatial and contextual information for the analysis of remote sensing images, especially for classification task. Since their first introduction to this field in early 2010’s, many research studies have been contributed not only to exploit and adapt their use to different applications, but also to extend and improve their performance for better dealing with more complex data. In this paper, we revisit and discuss different developments and extensions from APs which have drawn significant attention from researchers in the past few years. These studies are analyzed and gathered based on the concept of multi-stage AP construction. In our experiments, a comparative study on classification results of two remote sensing data is provided in order to show their significant improvement scompared to the originally proposed APs.

Recent developments from attribute profiles for remote sensing image classification / Pham, Minh-Tan; Lefèvre, Sébastien; Aptoula, Erchan; Bruzzone, Lorenzo. - (2018), pp. 102-107. (Intervento presentato al convegno ICPRAI 2018 tenutosi a Montréal nel 13th-17th May 2018).

Recent developments from attribute profiles for remote sensing image classification

Lorenzo Bruzzone
2018-01-01

Abstract

Morphological attribute profiles (APs) are among the most effective methods to model the spatial and contextual information for the analysis of remote sensing images, especially for classification task. Since their first introduction to this field in early 2010’s, many research studies have been contributed not only to exploit and adapt their use to different applications, but also to extend and improve their performance for better dealing with more complex data. In this paper, we revisit and discuss different developments and extensions from APs which have drawn significant attention from researchers in the past few years. These studies are analyzed and gathered based on the concept of multi-stage AP construction. In our experiments, a comparative study on classification results of two remote sensing data is provided in order to show their significant improvement scompared to the originally proposed APs.
2018
Proceedings of the International Conference on Pattern Recognition and Artificial Intelligence
Montreal, Quebec
CENPARMI
978-1-895193-04-6
Pham, Minh-Tan; Lefèvre, Sébastien; Aptoula, Erchan; Bruzzone, Lorenzo
Recent developments from attribute profiles for remote sensing image classification / Pham, Minh-Tan; Lefèvre, Sébastien; Aptoula, Erchan; Bruzzone, Lorenzo. - (2018), pp. 102-107. (Intervento presentato al convegno ICPRAI 2018 tenutosi a Montréal nel 13th-17th May 2018).
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