Volume 4 Issue 6
Dec.  2015
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Article Navigation >  Journal of Radars  > 2015  >  4(6): 658-665
Wang Lu, Zhang Fan, Li Wei, Xie Xiao-ming, Hu Wei. A Method of SAR Target Recognition Based on Gabor Filter and Local Texture Feature Extraction[J]. Journal of Radars, 2015, 4(6): 658-665. doi: 10.12000/JR15076
Citation: Wang Lu, Zhang Fan, Li Wei, Xie Xiao-ming, Hu Wei. A Method of SAR Target Recognition Based on Gabor Filter and Local Texture Feature Extraction[J]. Journal of Radars, 2015, 4(6): 658-665. doi: 10.12000/JR15076
shu

A Method of SAR Target Recognition Based on Gabor Filter and Local Texture Feature Extraction

DOI: 10.12000/JR15076

  • (College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China)

Funds:

The National Natural Science Foundation of China (61302164), The Fundamental Research Funds for the Central Universities (YS1404), The Beijing Higher Education Young Elite Teacher Project (YETP0500)

  • Received Date: 2015-06-17
  • Rev Recd Date: 2015-10-16
  • Publish Date: 2015-12-28
    Abstract
  • This paper presents a novel texture feature extraction method based on a Gabor filter and Three-Patch Local Binary Patterns (TPLBP) for Synthetic Aperture Rader (SAR) target recognition. First, SAR images are processed by a Gabor filter in different directions to enhance the significant features of the targets and their shadows. Then, the effective local texture features based on the Gabor filtered images are extracted by TPLBP. This not only overcomes the shortcoming of Local Binary Patterns (LBP), which cannot describe texture features for large scale neighborhoods, but also maintains the rotation invariant characteristic which alleviates the impact of the direction variations of SAR targets on recognition performance. Finally, we use an Extreme Learning Machine (ELM) classifier and extract the texture features. The experimental results of MSTAR database demonstrate the effectiveness of the proposed method.

     

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    • References(15)
  • [1]
    丁军, 刘宏伟, 王英华. 基于非负稀疏表示的SAR图像目标识别方法[J]. 电子与信息学报, 2014, 36(9): 2194-2200. Ding Jun, Liu Hong-wei, and Wang Ying-hua. SAR image target recognition based on non-negative sparse representation[J]. Journal of Electronics Information Technology, 2014, 36(9): 2194-2200.
    [2]
    梁胜杰, 张志华, 崔立林, 等. 基于主成分分析与核独立成分分析的降维方法[J]. 系统工程与电子技术, 2011, 33(9): 2144-2148. Liang Sheng-jie, Zhang Zhi-hua, Cui Li-lin, et al.. A reduced dimension method based on PCA and KICA[J]. Systems Engineering and Electronics, 2011, 33(9): 2144-2148.
    [3]
    周家锐, 纪震, 沈琳琳, 等. 基于Gabor小波与Memetic算法的人脸识别方法[J]. 电子学报, 2012, 40(4): 642-646. Zhou Jia-rui, Ji Zhen, Shen Lin-lin, et al.. Face recognition using Gabor wavelets and Memetic algorithm[J]. Acta Electronica Sinica, 2012, 40(4): 642-646.
    [4]
    高涛, 何明一, 戴玉超, 等. 多级LBP直方图序列特征的人脸识别[J]. 中国图象图形学报, 2009, 14(2): 202-207. Gao Tao, He Ming-yi, Dai Yu-chao, et al.. Face recognition using multi-level histogram sequence local binary pattern[J]. Journal of Image and Graphics, 2009, 14(2): 202-207.
    [5]
    Patel V, Nasraba N, and Chellappa R. Sparsity-motivated automatic target recognition[J]. Applied Optics, 2011, 50(10): 1425-1433.
    [6]
    Novak L M, Owirka G J, and Brower W S. Performance of 10-and 20-target MSE classification[J]. IEEE Transactions on Aerospace and Electronic Systems, 2000, 36(4): 1279-1289.
    [7]
    Li W and Du Q. Gabor-Filtering based nearest regularized subspace for hyperspectral image classification[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014, 7(4): 1012-1022.
    [8]
    Ojala T, Pietikainen M, and Maenpaa T. Multiresolution gray-scale and rotation invariant texture classification with local binary pattern[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002, 24(7): 971-987.
    [9]
    Lior W, Tal H, and Yaniv T. Descriptor based methods in the wild[C]. Real-Life Images Workshop at the European Conference on Computer Vision (ECCV), Marseille, France, 2008: 1-14.
    [10]
    张文博, 姬红兵. 融合极限学习机[J]. 电子与信息学报, 2013, 35(11): 2728-2732.
    [11]
    Zhang Wen-bo and Ji Hong-bing. Fusion of extreme learning machines[J]. Journal of Electronics Information Technology, 2013, 35(11): 2728-2732.
    [12]
    Zhou Y, Peng J, and Chen C. Extreme learning machine with composite kernels for hyperspectral image classification[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2015, 8(6): 2351-2360.
    [13]
    Moving and Stationary Target Acquisition and Recognition (MSTAR) Public Dataset[OL]. https://www.sdms.afrl. af.mil/datasets/mstar/.
    [14]
    尹奎英, 金林, 李成, 等. 融合目标轮廓和阴影轮廓的SAR 图像目标识别[J]. 空军工程大学学报(自然科学版), 2011, 12(1): 24-28.
    [15]
    Yin Kui-ying, Jin Lin, Li Cheng, et al.. An SAR ATR based on fusion of target contour and shadow contour[J]. Journal of Air Force Engineer University (Natural Science Edition), 2011, 12(1): 24-28.
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