A saliency-based ship target detection method in high sea state SAR images

doi:10.7523/j.ucas.2020.0050

Abstract

Abstract: In this study, a ship target detection method in high sea state SAR image, named Itti-SAR, based on saliency is proposed, which consists of two stages:saliency image extraction and connectivity judgment. In the stage of saliency map extraction, taking the characteristics of SAR images into consideration, the improved direction feature and consistency feature are introduced into the traditional visual attention model to construct a saliency model suitable for SAR images, which realizes the extraction of ship target saliency maps for high sea state SAR images. In the stage of connectivity judgment, the density constraint is used to judge the connectivity of salient areas to prevent the detection of a single target into multiple, thereby further reducing false alarms. The experimental results on several SAR images verify the effectiveness of the method. The experimental results show that compared with the classical CFAR algorithm, the proposed method has the advantages of high precision, high recall rate and independent of prior knowledge.

Key words: high sea state, SAR, ship detection, saliency

CLC Number:

TP753

ZHANG Ziqi, WANG Xiaolong. A saliency-based ship target detection method in high sea state SAR images[J]. Journal of University of Chinese Academy of Sciences, 2022, 39(5): 695-703.

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