Classification of multibeam sonar image using the Weyl transform
Zhao, T.; Lazendic, S.; Zhao, Y.; Montereale-Gavazzi, G.; Pižurica, A. (2020). Classification of multibeam sonar image using the Weyl transform, in: Choras, M. et al. Image processing and communications. Advances in Intelligent Systems and Computing, 1062: pp. 206-213. https://dx.doi.org/10.1007/978-3-030-31254-1_25
In: Choras, M.; Choras, R.S. (Ed.) (2020). Image processing and communications. Advances in Intelligent Systems and Computing, 1062. Springer: Cham. ISBN 978-3-030-31253-4; e-ISBN 978-3-030-31254-1. XII, 328 pp. https://dx.doi.org/10.1007/978-3-030-31254-1, meer
In: Advances in Intelligent Systems and Computing. Springer: Singapore. ISSN 2194-5357, meer
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| Beschikbaar in | Auteurs |
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Documenttype: Congresbijdrage
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| Trefwoord |
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| Author keywords |
Multibeam data processing; Multibeam sonar image; Feature extraction; Weyl transform; Acoustic sediment classification |
| Auteurs | | Top |
- Zhao, T., meer
- Lazendic, S., meer
- Zhao, Y.
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- Montereale-Gavazzi, G., meer
- Pižurica, A., meer
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| Abstract |
In this paper we develop a novel classification method for multibeam sonar images based on the Weyl transform. The texture descriptor based on Weyl coefficients describes effectively the multiscale correlation features appearing in the sonar images. Our classification approach combines the Weyl coefficients with statistical features that are commonly used in the analysis of seabed sonar images and captures the morphological variation and geoacoustic characteristics of the seafloor. We employ a neural network as a classifier. The proposed combined feature extraction method demonstrates better performance than the commonly used statistical methods in this application. |
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