Segmentation-based technique for ship detection in SAR images

Abstract

A novel segmentation-based ship detection scheme is proposed to cope with the typical features of sea clutter. In particular, it is shown that the standard 2D-CFAR schemes applied to both low- and high-resolution SAR images do not allow adequate control of the false-alarm rate for nonhomogeneity and non-gaussianity characteristics of back-scattering from the sea. The introduction of an appropriate first segmentation stage allows standard CFAR techniques to be applied inside homogeneous areas. Moreover, the derived approximate CFAR performance against non-gaussian clutter allows the detection threshold to be set to achieve the desired false alarm rate. The practical performance is demonstrated for both a set of low-resolution quick-look ERS-SAR images and a set of high-resolution single-look X-SAR/SIR-C images. This proved that the proposed segmentation-based scheme gives a very high ship detection capability for both sets, with a controlled number of false alarms in the presence of any structure or fluctuation of the background.