Modified Otsu´s algorithm: A new computationally efficient ship detection algorithm for SAR images

In the context of high spatial resolution Synthetic Aperture Radar (SAR) images, this paper deals with a new computationally efficient algorithm which allows us to accurately detect ships of certain dimensions, which can span in a range supposed known. The topic of ship detection in SAR imagery has been extensively analyzed in literature. However, little is known about such application on SAR data acquired by COSMO-SkyMed (CSK) satellite constellation. Commonly, in SAR images, ship detection methods rely on sea (background) statistical characterization. Nevertheless, such approaches typically require a high computational load. Thus, the time required by classic detection algorithms (e.g. Constant False Alarm Rate - CFAR) may become critical in the context of ship detection for maritime surveillance. In this paper we present a new computationally efficient algorithm for ship detection in SAR images, which is not a CFAR approach. Our algorithm is obtained modifying the classical two-classes segmentation provided by Otsu´s histogram thresholding algorithm. Such modifications are necessary to apply Otsu´s algorithm in SAR images. They are based on the geometrical proprieties of the target to be detected, i.e. ships whose dimensions can span in a range a priori known. Proofs of the goodness of our algorithm are given on a CSK image acquired over New York.