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Publication - Professor David Bull

    Superpixel-guided CFAR Detection of Ships at Sea in SAR Imagery

    Citation

    Pappas, OA, Achim, A & Bull, D, 2017, ‘Superpixel-guided CFAR Detection of Ships at Sea in SAR Imagery’. in: 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2017). Institute of Electrical and Electronics Engineers (IEEE), pp. 1647-1651

    Abstract

    Synthetic Aperture Radar (SAR) has over the years evolved to be one of the most promising remote sensing modalities for large-scale monitoring of the ocean and maritime activity. The detection of ships at sea in SAR imagery is a challenging task, as it requires the detection of small targets with little exploitable spatial information within a high resolution image. We present a novel method for the detection of ships based on superpixel segmentation and subsequent statistical characterisation, with no prior land masking. Our method acts as a bound to a CFAR detector, greatly reducing false positives. We present results on SENTINEL-1 imagery, demonstrating the detection performance of our algorithm.

    Full details in the University publications repository