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使用深度神经网络检测Cassini ISS图像中圆盘状星体轮廓

张庆丰 郑洋 成国豪 卢志聪 周晓妹 王宇辰

张庆丰, 郑洋, 成国豪, 卢志聪, 周晓妹, 王宇辰. 使用深度神经网络检测Cassini ISS图像中圆盘状星体轮廓[J]. 空间科学学报, 2020, 40(2): 289-295. doi: 10.11728/cjss2020.02.289
引用本文: 张庆丰, 郑洋, 成国豪, 卢志聪, 周晓妹, 王宇辰. 使用深度神经网络检测Cassini ISS图像中圆盘状星体轮廓[J]. 空间科学学报, 2020, 40(2): 289-295. doi: 10.11728/cjss2020.02.289
ZHANG Qingfen, ZHENG Yang, CHENG Guohao, LU Zhicong, ZHOU Xiaomei, WANG Yuchen. Contour Detection of Disk Resolved Objects in Cassini ISS Image Using Deep Neural Network[J]. Journal of Space Science, 2020, 40(2): 289-295. doi: 10.11728/cjss2020.02.289
Citation: ZHANG Qingfen, ZHENG Yang, CHENG Guohao, LU Zhicong, ZHOU Xiaomei, WANG Yuchen. Contour Detection of Disk Resolved Objects in Cassini ISS Image Using Deep Neural Network[J]. Journal of Space Science, 2020, 40(2): 289-295. doi: 10.11728/cjss2020.02.289

使用深度神经网络检测Cassini ISS图像中圆盘状星体轮廓

doi: 10.11728/cjss2020.02.289
基金项目: 

国家自然科学基金项目(U1431227,11873026),广东省自然科学基金项目(2016A030313092),广东省教育厅高等学校科技创新项目(2013KJCX0020)和中央高校基本科研业务费专项资金项目(21619413)共同资助

详细信息
    作者简介:

    张庆丰,E-mail:tqfz@jnu.edu.cn

  • 中图分类号: P121

Contour Detection of Disk Resolved Objects in Cassini ISS Image Using Deep Neural Network

  • 摘要: Cassini空间探测器光学成像系统(ISS)拍摄的图像中,很多卫星呈现为面元,其轮廓检测是天体测量的重要工作.使用神经网络方法进行ISS图像中面元轮廓检测.每个ISS图像的像素分为轮廓边缘和非轮廓两类.使用神经网络框架TensorFlow,输入每个像素的9个特征,输出每个像素的分类.利用约3.6万个像素训练该网络,通过380幅ISS图像进行测试.与人工标记结果相比,轮廓像素检测的平均精确率为78.26%,平均召回率为73.32%.以检出轮廓像素作为输入,通过椭圆拟合得到面元的轮廓,所得轮廓与面元真实轮廓吻合良好.研究结果表明该方案能够有效检测出面元轮廓,进而给出假图像星的排除范围.

     

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出版历程
  • 收稿日期:  2018-09-03
  • 修回日期:  2019-08-02
  • 刊出日期:  2020-03-15

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