Automatic Ship Detection in SAR Images Using Multi-Scale Heterogeneities and an A Contrario Decision

Remote Sensing

Xiaojing Huang¹  Wen Yang¹  Haijian Zhang¹  Gui-Song Xia²  Gonzalo Pajares Martinsanz³ 

[1] School of Electronic Information, Wuhan University, Wuhan 430072, China; E-Mails:;State Key Laboratory of LIESMARS, Wuhan University, Wuhan 430079, China; E-Mail:School of Electronic Information, Wuhan University, Wuhan 430072, China;

关键词: synthetic aperture radar;    ship detection;    heterogeneity feature;    a contrario decision;   

DOI  :  10.3390/rs70607695

来源: mdpi

【 摘 要 】

The robust detection of ships is one of the key techniques in coastal and marine applications of synthetic aperture radar (SAR). Conventional SAR ship detectors involved multiple parameters, which need to be estimated or determined very carefully. In this paper, we propose a new ship detection approach based on multi-scale heterogeneities under the a contrario decision framework, with a few parameters that can be easily determined. First, multi-scale heterogeneity features are extracted and fused to build a heterogeneity map, in which ships are well highlighted from backgrounds. Second, a set of reference objects are automatically selected by analyzing the saliency of local regions in the heterogeneity map and then are used to construct a null hypothesis model for the final decision. Finally, the detection results are obtained by using an a contrario decision. Experimental results on real SAR images demonstrate that the proposed method not only works more stably for ships with different sizes, but also has better performance than conventional ship detectors.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland