Ship Detection in Multispectral Remote Sensing Images via Saliency Analysis

Abstract

Despite the increasing visible optical remote sensing cameras equipped with panchromatic and four-band multispectral sensors, the application of multispectral data is still rarely used in the field of remote sensing ship target detection with the openly recognized challenge to improve detection precision. Towards this end, a ship target saliency detection method is proposed in the paper, which combines weighted least squares (WLS) with maximum symmetric surround (MSS), based on RGB-NIR four-band multispectral remote sensing images to locate the candidate area of ship targets quickly and accurately. The high frequency information of the NIR band image is extracted through the WLS filter and integrated into the RGB band image, and then the saliency of the image is analyzed. The detection results are combined with AIS to achieve complementary information for ship recognition. Some experiments show that the proposed method can effectively suppress the complex background information of clutter interference such as cloud waves and sea waves, highlight the ship target in low contrast scenes, and also increase recall and precision effectively.