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Markov-based approaches for ternary change detection between two high resolution synthetic aperture sonar tracks

Florian Nicolas 1 Andreas Arnold-Bos 1 Isabelle Quidu 2, 3 Benoit Zerr 2, 3
2 Lab-STICC_ENSTAB_CID_PRASYS
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
3 Pôle STIC_OSM
ENSTA Bretagne - École Nationale Supérieure de Techniques Avancées Bretagne
Abstract : Change detection methods, consisting in detecting potential changes between two images, representing the same geographical area but acquired at different times, have been widely used in sonar imagery. Such methods are very useful to accurately monitor, potentially low, variations in complex environments. Coherent methods, relying on both amplitude and phase of the backscattered signal, are limited because of the signals correlation that plummets with both frequency and temporal baseline. In this paper, we propose an incoherent method, only using the amplitude images, to solve the change detection problem. This method relies on a robust mathematical expression for the class conditional probability density functions of the log-ratio image along with various Markov-based approaches to provide a ternary change map, thus allowing to better understand the changes that have occured on the seafloor.
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https://hal-ensta-bretagne.archives-ouvertes.fr/hal-01702377
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Soumis le : vendredi 9 février 2018 - 11:15:48
Dernière modification le : mardi 25 février 2020 - 08:08:14

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Florian Nicolas, Andreas Arnold-Bos, Isabelle Quidu, Benoit Zerr. Markov-based approaches for ternary change detection between two high resolution synthetic aperture sonar tracks. OCEANS 2017, IEEE, Jun 2017, Aberdeen, United Kingdom. ⟨10.1109/OCEANSE.2017.8084766⟩. ⟨hal-01702377⟩

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