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宽带电磁图像卷积神经网络盲恢复方法研究

朱艳菊 谢树果 李元豪 张娴

朱艳菊, 谢树果, 李元豪, 等. 宽带电磁图像卷积神经网络盲恢复方法研究[J]. 强激光与粒子束, 2019, 31: 103210. doi: 10.11884/HPLPB201931.190191
引用本文: 朱艳菊, 谢树果, 李元豪, 等. 宽带电磁图像卷积神经网络盲恢复方法研究[J]. 强激光与粒子束, 2019, 31: 103210. doi: 10.11884/HPLPB201931.190191
Zhu Yanju, Xie Shuguo, Li Yuanhao, et al. Research on blind recovery method of wideband electromagnetic image convolutional neural network[J]. High Power Laser and Particle Beams, 2019, 31: 103210. doi: 10.11884/HPLPB201931.190191
Citation: Zhu Yanju, Xie Shuguo, Li Yuanhao, et al. Research on blind recovery method of wideband electromagnetic image convolutional neural network[J]. High Power Laser and Particle Beams, 2019, 31: 103210. doi: 10.11884/HPLPB201931.190191

宽带电磁图像卷积神经网络盲恢复方法研究

doi: 10.11884/HPLPB201931.190191
基金项目: 

国家自然科学基金项目 61427803

详细信息
    作者简介:

    朱艳菊(1985—),女,博士研究生,从事电磁兼容、电磁图像处理、散射计算方面的研究; zhuyanju1309@163.com

  • 中图分类号: TP391

Research on blind recovery method of wideband electromagnetic image convolutional neural network

  • 摘要: 在利用抛物反射面对电磁干扰源成像过程中,由于系统衍射受限及成像频带较宽,导致干扰源成像模糊,分辨率低,难以分辨,不同频率不同区域干扰源所成图像分辨率不同,采用已有超分辨算法难以提高分辨率。为了实现宽带电磁图像的盲复原, 应用卷积神经网络的方法。网络训练是直接输入模糊图像,不假设任何特定的模糊和噪声模型情况下,重建出高质量图像。实验和仿真结果证明了卷积神经网络盲恢复方法在宽频带不同成像区域下表现了优于其他盲恢复算法的优势。
  • 图  1  算法网络结构示意图

    Figure  1.  Schematic diagram of algorithm network structure

    图  2  仿真图像三种算法结果对比

    Figure  2.  Comparison of three algorithms for simulation images

    图  3  不同噪声下三种算法结果图

    Figure  3.  Results of three algorithms under different noises

    图  4  2 GHz两干扰源图像恢复效果图

    Figure  4.  Diagram of 2 GHz two-interference-source image restoration effect

    图  5  4 GHz两干扰源图像恢复效果图

    Figure  5.  Diagram of 4 GHz two-interference-source image restoration effect

    图  6  6 GHz两干扰源图像恢复效果图

    Figure  6.  Diagram of 6 GHz two-interference-source image restoration effect

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    Li Liangchao, Yang Jianyu, Zheng Xin, et al. Research on passive millimeter wave image super-resolution algorithm and real-time implementation. Journal of University of Electronic Science and Technology of China, 2009, 38(6): 952-956 https://www.cnki.com.cn/Article/CJFDTOTAL-DKDX200906012.htm
    [2] 杜鑫, 谢树果, 郝旭春, 等. 一种电磁干扰源成像多分辨率分区算法[J]. 强激光与粒子束, 2015, 27: 103223. doi: 10.11884/HPLPB201527.103223

    Du Xin, Xie Shuguo, Hao Xuchun, et al. An electromagnetic interference source imaging algorithm of multi-resolution partitions. High Power Laser and Particle Beams, 2015, 27: 103223 doi: 10.11884/HPLPB201527.103223
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    Li Yuanjiang, Li Yuehua, Zhang Guangfeng. A modified method of super-resolution restoration for passive millimeter wave images. Modern Radar, 2011, 33(8): 43-46 https://www.cnki.com.cn/Article/CJFDTOTAL-XDLD201108013.htm
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出版历程
  • 收稿日期:  2019-05-30
  • 修回日期:  2019-06-17
  • 刊出日期:  2019-10-15

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