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A Novel Polarization Scattering Decomposition Model and Its Application to Ship Detection.
In: Remote Sensing, Jg. 16 (2024), Heft 1, S. 178-199
Online
academicJournal
Zugriff:
In polarimetric synthetic aperture radar (POLSAR), it is of great significance for civil and military applications to find novel model-based decomposition methods suitable for ship detection in different detection backgrounds. Based on the physical interpretation of polarimetric decomposition theory and the Lasso rule for sparse features, we propose a four-component decomposition model, which is composed of surface scattering (Odd), double-bounce scattering (Dbl), volume scattering (Vol), and ±45° oriented dipole (Od). In principle, the Od component can describe the compounded scattering structure of a ship consisting of odd-bounce and even-bounce reflectors. Moreover, the pocket perceptron learning algorithm (PPLA) and support vector machine (SVM) are utilized to solve the linear inseparable problems in this study. Using large amounts of RADARSAT-2 (RS-2) fully polarized SAR data and AIRSAR data, our experimental results show that the Od component can make a great contribution to ship detection. Compared with other conventional decomposition methods used in the experiments, the proposed four-component decomposition method has better performance and is more effective and feasible to detect ships. [ABSTRACT FROM AUTHOR]
Titel: |
A Novel Polarization Scattering Decomposition Model and Its Application to Ship Detection.
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Autor/in / Beteiligte Person: | Fang, Lu ; Yang, Ziyuan ; Mu, Wenxing ; Liu, Tao |
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Zeitschrift: | Remote Sensing, Jg. 16 (2024), Heft 1, S. 178-199 |
Veröffentlichung: | 2024 |
Medientyp: | academicJournal |
ISSN: | 2072-4292 (print) |
DOI: | 10.3390/rs16010178 |
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