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基于生成式对抗网络的太赫兹图像增强

张鹏程 何明霞 陈硕 张洪桢 张欣欣

张鹏程, 何明霞, 陈硕, 张洪桢, 张欣欣. 基于生成式对抗网络的太赫兹图像增强[J]. 红外技术, 2021, 43(4): 391-396.
引用本文: 张鹏程, 何明霞, 陈硕, 张洪桢, 张欣欣. 基于生成式对抗网络的太赫兹图像增强[J]. 红外技术, 2021, 43(4): 391-396.
ZHANG Pengcheng, HE Mingxia, CHEN Shuo, ZHANG Hongzhen, ZHANG Xinxin. Terahertz Image Enhancement Based on Generative Adversarial Network[J]. Infrared Technology , 2021, 43(4): 391-396.
Citation: ZHANG Pengcheng, HE Mingxia, CHEN Shuo, ZHANG Hongzhen, ZHANG Xinxin. Terahertz Image Enhancement Based on Generative Adversarial Network[J]. Infrared Technology , 2021, 43(4): 391-396.

基于生成式对抗网络的太赫兹图像增强

详细信息
    作者简介:

    张鹏程(1995-),男,河南周口人,硕士生,研究方向为太赫兹成像及图像处理,E-mail:1298216729@qq.com

  • 中图分类号: TP751

Terahertz Image Enhancement Based on Generative Adversarial Network

  • 摘要: 太赫兹扫描成像中,由于激光器功率波动和仪器振动等原因,导致图像对比度较低,成像质量有待提高,且目前针对太赫兹图像的处理还停留在传统算法阶段。本文结合深度学习思想,提出了一种基于生成式对抗网络的图像增强方法。通过对训练集图像引入模糊和噪声,学习低质量图像和高质量图像之间的映射关系,并将其应用在真实太赫兹图像中。实验结果表明,与双边滤波、非局部均值滤波等传统算法相比,本文方法可在改善图像细节的基础上显著提高图像对比度,且视觉体验良好,这为太赫兹图像增强提供了新思路。
  • 图  1  GAN流程图

    Figure  1.  Flow chart of GAN

    图  2  SRGAN网络框架结构

    Figure  2.  Framework of SRGAN

    图  3  图像数据集示例

    Figure  3.  Image dataset example

    图  4  训练过程中曲线变化

    Figure  4.  Variation curves change during training

    图  5  不同算法实验结果比较

    Figure  5.  Comparison of experimental results of different algorithms

    表  1  不同方法PSNR、对比度计算结果

    Table  1.   PSNR and contrast calculation results by differentmethods

    Bilateral filtering Nonlocal mean filtering Our algorithm
    PSNR 28.18 26.87 25.28
    Contrast 178.69 134.48 375.98
    下载: 导出CSV
  • [1] 郑显华, 王新柯, 孙文峰, 等. 太赫兹数字全息术的研发与应用[J]. 中国激光, 2014, 41(2): 0209003. https://www.cnki.com.cn/Article/CJFDTOTAL-JJZZ201402004.htm

    ZHENG Xianhua, WANG Xinke, SUN Wenfeng, et al. Developments and applications of the terahertz digital holography[J]. Chinese J. Lasers, 2014, 41(2): 0209003. https://www.cnki.com.cn/Article/CJFDTOTAL-JJZZ201402004.htm
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    ZHANG Xin, ZHAO Yuanmeng, ZHANG Cunlin. Passive terahertz image segmentation algorithm[J]. High Power Laser and Particle Beams, 2013, 25(6): 1597-1600. https://www.cnki.com.cn/Article/CJFDTOTAL-QJGY201306056.htm
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    LI Qi, YANG Yongfa, HU Jiaqi. A composite algorithm used for terahertz confocal scanning image restoration[J]. Infrared and Laser Engineering, 2015, 44(1): 321-326. doi:  10.3969/j.issn.1007-2276.2015.01.055
    [5] 杨永发, 李琦. 双边滤波算法的太赫兹共焦扫描图像去噪应用[J]. 激光与光电子学进展, 2015, 52(12): 121101. https://www.cnki.com.cn/Article/CJFDTOTAL-JGDJ201512015.htm

    YANG Yongfa, LI Qi. Application of bilateral filtering algorithm on terahertz confocal scanning image denoising[J]. Laser & Optoelectronics Progress, 2015, 52(12): 121101. https://www.cnki.com.cn/Article/CJFDTOTAL-JGDJ201512015.htm
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    [8] 卢贺洋, 苏胜君, 袁明辉, 等. 太赫兹图像的超分辨率重建[J]. 红外技术, 2019, 41(1): 59-63. http://hwjs.nvir.cn/article/id/hwjs201901009

    LU Heyang, SU Shengjun, YUN Minghui, et al. Super-resolution reconstruction of terahertz image[J]. Infrared Technology, 2019, 41(1): 59-63. http://hwjs.nvir.cn/article/id/hwjs201901009
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出版历程
  • 收稿日期:  2019-09-29
  • 修回日期:  2019-11-04
  • 刊出日期:  2021-04-20

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