The automatic analysis of radargrams acquired by radar sounder instruments is an important task, as it has been often highlighted by the scientific community. In particular, an automatic classification technique enables a fast and objective extraction of ice subsurface target properties on wide areas. The main drawback of the available classification techniques is the use of fixed size windows for feature extraction, which causes a poor classification performance at the transition boundary between adjacent subsurface targets. To address this issue, in this paper, we propose a novel technique for the automatic classification of ice subsurface targets in radargrams. The method provides two key contributions, i.e., i) the use of a window size estimation method to adaptively characterize the subsurface targets, and ii) the use of the estimated windows for extracting novel discriminant features for automatic classification. Quantitative and qualitative results obtained by applying the method to a data set of radargrams acquired by an airborne-mounted radar sounder instrument in central Antarctica show the effectiveness of the proposed technique, which outperforms previously proposed methods.

A technique based on adaptive windows for the classification of radar sounder data / Khodadadzadeh, Mahdi; Ilisei, Ana-Maria; Bruzzone, Lorenzo. - ELETTRONICO. - (2017), pp. 3739-3742. ((Intervento presentato al convegno International Geoscience and Remote Sensing Symposium 2017 (IGARSS 2017) tenutosi a Fort Worth, Texas, USA nel July 23–28, 2017 [10.1109/IGARSS.2017.8127812].

A technique based on adaptive windows for the classification of radar sounder data

Khodadadzadeh, Mahdi;Ilisei, Ana-Maria;Bruzzone, Lorenzo
2017

Abstract

The automatic analysis of radargrams acquired by radar sounder instruments is an important task, as it has been often highlighted by the scientific community. In particular, an automatic classification technique enables a fast and objective extraction of ice subsurface target properties on wide areas. The main drawback of the available classification techniques is the use of fixed size windows for feature extraction, which causes a poor classification performance at the transition boundary between adjacent subsurface targets. To address this issue, in this paper, we propose a novel technique for the automatic classification of ice subsurface targets in radargrams. The method provides two key contributions, i.e., i) the use of a window size estimation method to adaptively characterize the subsurface targets, and ii) the use of the estimated windows for extracting novel discriminant features for automatic classification. Quantitative and qualitative results obtained by applying the method to a data set of radargrams acquired by an airborne-mounted radar sounder instrument in central Antarctica show the effectiveness of the proposed technique, which outperforms previously proposed methods.
Proceedings on IEEE Xplore
USA, Piscataway, NJ 088
Institute of Electrical and Electronics Engineers Inc.
978-1-5090-4951-6
Khodadadzadeh, Mahdi; Ilisei, Ana-Maria; Bruzzone, Lorenzo
A technique based on adaptive windows for the classification of radar sounder data / Khodadadzadeh, Mahdi; Ilisei, Ana-Maria; Bruzzone, Lorenzo. - ELETTRONICO. - (2017), pp. 3739-3742. ((Intervento presentato al convegno International Geoscience and Remote Sensing Symposium 2017 (IGARSS 2017) tenutosi a Fort Worth, Texas, USA nel July 23–28, 2017 [10.1109/IGARSS.2017.8127812].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/193506
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