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Proceedings Paper

Synthetic aperture radar automatic target recognition based on curvelet transform
Author(s): Shuang Wang; Zhuo Liu; Licheng Jiao; Jun He
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Paper Abstract

A novel synthetic aperture radar (SAR) automatic target recognition (ATR) approach based on Curvelet Transform is proposed. However, the existing approaches can not extract the more effective feature. In this paper, our method is concentrated on a new effective representation of the moving and stationary target acquisition and recognition (MSTAR) database to obtain a more accurate target region and reduce feature dimension. Firstly, MSTAR database can be extracted feature through the optimal sparse representation by curvelets to obtain a clear target region. However, considering the loss of part of edges of image. We extract coarse feature, which is to compensate fine feature error brought by segmentation. The final features consisting of fine and coarse feature are classified by SVM with Gaussian radial basis function (RBF) kernel. The experiments show that our proposed algorithm can achieve a better correct classification rate.

Paper Details

Date Published: 30 October 2009
PDF: 7 pages
Proc. SPIE 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis, 74951K (30 October 2009); doi: 10.1117/12.832815
Show Author Affiliations
Shuang Wang, Xidian Univ. (China)
Zhuo Liu, Xidian Univ. (China)
Licheng Jiao, Xidian Univ. (China)
Jun He, Xidian Univ. (China)


Published in SPIE Proceedings Vol. 7495:
MIPPR 2009: Automatic Target Recognition and Image Analysis
Tianxu Zhang; Bruce Hirsch; Zhiguo Cao; Hanqing Lu, Editor(s)

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