Design and Evaluation of a Artificial Intelligence Based Vessel Detection System in Pol-SAR Images

Conference: EUSAR 2018 - 12th European Conference on Synthetic Aperture Radar
06/04/2018 - 06/07/2018 at Aachen, Germany

Proceedings: EUSAR 2018

Pages: 5Language: englishTyp: PDF

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Benito-Ortiz, Mari-Cortes; Mata-Moya, D.; Jarabo-Amores, M. P.; Rey-Maestre, N. del; Barcena-Humanes, J. L. (Signal Theory and Communications Department. Superior Polytechnic School, University of Alcala, Spain)

This paper tackles the design and evaluation of a vessel detection system based on intelligent agents that allow the jointly exploitation of statistical information from polarimetric SAR (Syntehtic Aperture Radar) images. Multilayer Perceptron (MLP) and cost-sensitive Support Vector Machine (2C-SVM) are considered to study the suitability of the best architecture. Detection performances are compared to a CFAR (Constant False Alarm Rate) detector based on a Generalized Γ Distribution sea clutter model and an OR-logic post-detection combination. Regardless the intelligent agent architecture, the proposed detectors outperforms the reference one resulting the 2C-SVM detector slightly better than MLP solution.