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Proceedings Paper

Ship detection in low-resolution SAR images based on background suppression
Author(s): Weidong Yang; Tianxu Zhang; Yunsheng Liu
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Paper Abstract

Owing to the capabilities of time and weather independent imaging, Synthetic Aperture Radar (SAR) is one of the most promising remote sensors for ship detection in the field of ocean surveillance. Low-resolution SAR imaging sensor provides wide area coverage, which is useful for monitoring large expanses of coastal waters for the presence of ships. In low-resolution SAR images, the ship detection belongs to small target detection problem in speckle noise image. The background suppression method against the typical features of generic non-homogeneous sea clutter and the strong background noise should be a crucial step in the object detection. A background inhibition network model is firstly built on the theory about the lateral inhibition of biological visions. Secondly, a novel region of interest (ROI) extraction method based on the Renyi's entropy is proposed. Finally, a homogeneity-testing method to reduce the false ship target of ROI is suggested, which was by the means of statistical distribution function of intensity variance-mean ratio (VMR) in homogeneity. The experimental results demonstrated that the lateral inhibition method can not only suppress the background and clutters well, but also can enhance the ship target perfectly. The proposed algorithm has good performance in adapt to various sea-condition and observing angle.

Paper Details

Date Published: 15 November 2007
PDF: 8 pages
Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 67864Z (15 November 2007); doi: 10.1117/12.774735
Show Author Affiliations
Weidong Yang, Huazhong Univ. of Science and Technology (China)
Tianxu Zhang, Huazhong Univ. of Science and Technology (China)
Yunsheng Liu, Huazhong Univ. of Science and Technology (China)

Published in SPIE Proceedings Vol. 6786:
MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition
Tianxu Zhang; Tianxu Zhang; Carl Anthony Nardell; Carl Anthony Nardell; Hanqing Lu; Duane D. Smith; Hangqing Lu, Editor(s)

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