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Proceedings Paper

Ship detection algorithm in SAR images based on Alpha-stable model
Author(s): Changcheng Wang; Mingsheng Liao; Xiaofeng Li; Liming Jiang; Xinjun Chen
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Paper Abstract

This paper proposes a new ship detection algorithm based on Alpha-stable model for detection ships in the spaceborne synthetic aperture radar (SAR) images. The current operational ship detection algorithm is based on Constant False Alarm Rate (CFAR) method. The major shortcoming of this method is that it requires an appropriate model to describe statistical characteristic of background clutter. For multilook SAR images, the Gaussian model can be used. However, the Gaussian model is only valid when several radar looks are averaged. As sea clutter in SAR images shows spiky or heavy-tailed characteristics, the Gaussian model often fails to describe background sea clutter. In this study, we replace Gaussian model with Alpha-stable model, which is widely used in the application of impulsive or spiky signal processing, to describe the background sea clutter in SAR images. Similar to the typical Two-parameter CFAR algorithm based on Gaussian distribution, we move a set of local windows through the image and finds bright pixels that are statistically different than the surrounding sea clutter. Several RADARSAT-1 images are used to validate this Alpha-stable model based algorithm. The experimental results show improvements of using Alpha-stable model over the Gaussian model.

Paper Details

Date Published: 15 November 2007
PDF: 7 pages
Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 678611 (15 November 2007); doi: 10.1117/12.747389
Show Author Affiliations
Changcheng Wang, Wuhan Univ. (China)
Mingsheng Liao, Wuhan Univ. (China)
Xiaofeng Li, NOAA Science Ctr. (United States)
Shanghai Fisheries Univ. (China)
Liming Jiang, Wuhan Univ. (China)
Chinese Univ. of Hong Kong (Hong Kong China)
Xinjun Chen, Shanghai Fisheries Univ. (China)


Published in SPIE Proceedings Vol. 6786:
MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition

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