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Volume 28 Issue 10
Sep.  2010
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Zhang Qi, Gao Gui, Kuang Gang-yao. A Fusion Method for Target Detection in SAR Image[J]. Journal of Electronics & Information Technology, 2006, 28(10): 1802-1805.
Citation: Zhang Qi, Gao Gui, Kuang Gang-yao. A Fusion Method for Target Detection in SAR Image[J]. Journal of Electronics & Information Technology, 2006, 28(10): 1802-1805.

A Fusion Method for Target Detection in SAR Image

  • Received Date: 2005-01-20
  • Rev Recd Date: 2005-07-22
  • Publish Date: 2006-10-19
  • A method fused by Extended Fractal (EF) feature and local contract feature is proposed for target detection in SAR image. The paper mainly discussed the size sensitivity behavior for the EF feature and the second-order statistics for the EF feature in various target/clutter models, and concluded that the feature is also invariant to negative scalar multiplication of the image in the sense that a deep target-sized shadow can also be detected as well as bright target-sized objects. While the CFAR method only using the local contract information is not symmetric, it has a high false alarm in the strong clutter environment. Fusion of the two features provides an even lower false alarm rate when the targets can be detected. Experiments with real data show the effective of the fusion method.
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  • 何友, 关键, 彭应宁.雷达自动检测与恒虚警处理. 北京: 清华大学出版社,1999: 32.136.[2]Mandelbrot B B. The Fractal Geometry of Nature. San Francisco: Freeman,1982.[3]Kaplan L M, Kuo C C J. Texture roughness analysis and synthesis via extended self-similar (ESS) model[J].IEEE Trans. on Pattern Analysis and Machine Intelligence.1995, 17(11):1043-[4]Kaplan L M. Improved SAR target detection via extended fractal . IEEE Trans. on AES, 2001, 37(4): 436451. .[5]Novak L M, Halversen S D, Owirka G J, Hiett M. Effects of polarization and resolution on SAR ATR. IEEE Trans. on AES, 1997, 33(1): 49.68.[6]Quoc H.Pham Timothy M Brosnan, Mark J T Smith. Mutristage algorithm for detection of targets in SAR Image Data. SPIE 1997,Vol.3070,: 66.75.
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