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相位差波前探测与图像重建

张杏云 罗芳琳 李楠 杨程亮 彭增辉 穆全全

张杏云, 罗芳琳, 李楠, 等. 相位差波前探测与图像重建[J]. 强激光与粒子束, 2021, 33: 081010. doi: 10.11884/HPLPB202133.210203
引用本文: 张杏云, 罗芳琳, 李楠, 等. 相位差波前探测与图像重建[J]. 强激光与粒子束, 2021, 33: 081010. doi: 10.11884/HPLPB202133.210203
Zhang Xingyun, Luo Fanglin, Li Nan, et al. Phase diversity wavefront sensing and image reconstruction[J]. High Power Laser and Particle Beams, 2021, 33: 081010. doi: 10.11884/HPLPB202133.210203
Citation: Zhang Xingyun, Luo Fanglin, Li Nan, et al. Phase diversity wavefront sensing and image reconstruction[J]. High Power Laser and Particle Beams, 2021, 33: 081010. doi: 10.11884/HPLPB202133.210203

相位差波前探测与图像重建

doi: 10.11884/HPLPB202133.210203
基金项目: 国家自然科学基金项目(61805238;11774342);中国科学院创新交叉团队项目
详细信息
    作者简介:

    张杏云(1988—),男,博士,副研究员,从事自适应光学及新型光器件研究

    通讯作者:

    穆全全(1980—),男,博士,研究员,从事自适应光学及液晶光学研究

  • 中图分类号: O439

Phase diversity wavefront sensing and image reconstruction

  • 摘要: 相位差技术可以直接利用两幅或多幅图像的强度信息,重构出波前相位信息和目标清晰图像,具有光路简单、成本较低、适用于扩展目标等优点,在望远镜的系统像差检测和目标图像重建方面得到了大量应用。相位差波前探测的关键在于求解非线性代价函数的最优化问题,需要避免陷入局部极值并降低计算时间,才能满足动态变化波前实时探测的需求。同时在重建目标清晰图像时,通常需要做正则化和去噪处理,来提高重建图像的质量。本文主要介绍相位差技术的基本原理,以及近年来的研究进展,并对该技术未来的发展进行了展望。
  • 图  1  离焦作为相位差函数的PD技术示意图

    Figure  1.  Schematic diagram of PD technology with defocus as the phase diversity function

    图  2  代价函数具有单个极值(a)和多个极值(b)的示意图

    Figure  2.  Schematic diagram of cost function with single extremum (a) and multiple extremum (b)

    图  3  三种不同波前幅值的实验结果:从左至右分别为焦面图像、离焦面图像、重建相位和重建图像

    Figure  3.  Experimental results of three different wavefront amplitudes: (from left to right) focal plane images, defocus plane images, reconstructed phases and reconstructed images

    图  4  粒子群算法的迭代方向

    Figure  4.  Iterative direction of particle swarm optimization

    图  5  基于LSTM网络的相位差波前探测

    Figure  5.  Phase diversity wavefront sensing based on LSTM network

    图  6  基于卷积神经网络的相位差波前探测

    Figure  6.  Phase diversity wavefront sensing based on convolution neural network

    图  7  第一行:焦面图像;第二行:未去噪重建图像;第三行:去噪后重建图像

    Figure  7.  First line: focal plane images; Second line: reconstructed images without denoising; Third line: reconstructed images after denoising

    图  8  PD标定NFIRAOS系统非共光路像差

    Figure  8.  Calibration of non-common path aberrations in NFIRAOS system with PD technology

    图  9  太阳观测结果:左-PD恢复前;右-PD恢复后

    Figure  9.  Solar observation data: (left) unreconstructed image; (right) PD reconstructed image

    图  10  1.2 m望远镜白天对国际空间站的成像结果:左-PD恢复前;右-PD恢复后

    Figure  10.  Daytime observation of the International Space Station: (left) unreconstructed image; (right) PD reconstructed image

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出版历程
  • 收稿日期:  2021-05-28
  • 修回日期:  2021-08-10
  • 网络出版日期:  2021-08-26
  • 刊出日期:  2021-08-15

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