Ship detection in SAR images by saliency analysis of multiscale superpixels

This paper proposes a new ship detection algorithm via saliency analysis on multiscale superpixels. First, Synthetic Aperture Radar (SAR) imagery is over-segmented into many homogenous regions, called superpixels. In contrast to prior work, these superpixels are generated with various scales to handle size variation of ships in the SAR imagery. At each scale, local contrast and ship geometrical characteristics are considered to enhance the saliency of ship pixels. Then, the final saliency map is computed by integrating saliency values of all scales. Experimental results on two real SAR images demonstrate the efficiency of the proposed algorithm.

Automated summary

This paper proposes a ship detection algorithm based on saliency analysis using multiscale superpixels. By over-segmenting SAR imagery into superpixels of various scales and considering local contrast and ship geometrical characteristics, the algorithm efficiently extracts the saliency information of ships.