Texture Feature Extraction and Analyses for Mobile Targets in High-Resolution SAR Imagery

Li  Yu; Liu  Jun; Ji  Ke-Feng; Su  Yi

doi:10.3724/SP.J.1146.2007.01059

Volume 30 Issue 12

Jan. 2011

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Article Navigation > Journal of Electronics & Information Technology > 2008 > 30(12): 2809-2812

Li Yu, Liu Jun, Ji Ke-Feng, Su Yi. Texture Feature Extraction and Analyses for Mobile Targets in High-Resolution SAR Imagery[J]. Journal of Electronics & Information Technology, 2008, 30(12): 2809-2812. doi: 10.3724/SP.J.1146.2007.01059

Citation:

Li Yu, Liu Jun, Ji Ke-Feng, Su Yi. Texture Feature Extraction and Analyses for Mobile Targets in High-Resolution SAR Imagery[J]. Journal of Electronics & Information Technology, 2008, 30(12): 2809-2812. doi: 10.3724/SP.J.1146.2007.01059

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Texture Feature Extraction and Analyses for Mobile Targets in High-Resolution SAR Imagery

doi: 10.3724/SP.J.1146.2007.01059

Li Yu^{①② 刘军
,},
Liu Jun,
Ji Ke-Feng,
Su Yi

Received Date: 2007-06-29
Rev Recd Date: 2007-12-31
Publish Date: 2008-12-19

Abstract

Abstract

Based on the theory of scattering center, the difference of back-scattering characteristics between the mobile targets and natural terrains in high-resolution SAR imagery is investigated, and the principles of texture features of the two kind targets are discussed in this paper. And then, the texture features are extracted by using respectively the local statistics and fractal models, and the method of selecting the best features is presented. The real vehicle target SAR image data in MSTAR database are used to test the texture features, the best features are selected and the discriminating performances of those features are shown. The results show that those features are good and can be used to eliminate the most false alarms of natural terrains.
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References(1)

References

[1] Oliver C and Quegan S. Understanding Synthetic ApertureRadar Images. Boston, London, Artech House, 1998:277-296. [2] Lee C P and Randolph L M. Attributed scattering centersfor SAR ATR[J].IEEE Trans. on Image Processing.1997,6(1):79-91 [3] Gan Du and Tat Soon Yeo. A novel lacunarity estimationmethod applied to SAR image segmentation[J].IEEE Trans.on Geoscience and Remote Sensing.2002, 40(12):2687-2691 [4] Kreithen D E, Halversen S D, and Owirka G J.Discriminating targets from clutter. Lincoln LaboratoryJournal, 1993, 6(1): 25-52. [5] Novak L M, Halversen S D, and Owirka G J, et al.. Effectsof polarization and resolution on SAR ATR[J].IEEE Trans.on Aerospace and Electronic Systems.1997, 33(1):102-116 [6] Zhang Cui, Zou Tao, and Wang Zhengzhi. A targetdiscrimination algorithm for high resolution SAR imagery.IEEE Proceeding of International Conference on Robotics,Intelligent Systems and Signal Processing, Changsha,China, 2003: 863-867. [7] Myint Soe Win and Lam Nina. A study of lacunarity-basedtexture analysis approaches to improve urban imageclassification[J].Computers, Environment and Urban Systems.2005, 29(5):501-523 [8] Dong P. Test of a new lacunarity estimation method forimage texture analysis. International Journal of RemoteSensing, 2000, 21(17): 3369-3373.

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