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At present, in the experiment on inertial confinement fusion (ICF), no single imaging diagnosis of the black cavity plasma or the implosion target region can distinguish the emission intensity information in the depth direction, that is, the images acquired by the detector are intensity integral along the detection direction. In this paper, a tomographic imaging method using incoherent holography for microscale X-ray source is introduced. The incoherent holographic imaging technology has an imaging mechanism that encodes and compresses the three-dimensional space information of the light source into a two-dimensional hologram. In the theoretical part, we examine the imaging mechanism of incoherent holographic tomography. Then the compress sensing model which is appropriate for this incoherent tomography is investigated. Combined with the hologram reconstruction algorithm based on compress sensing, the two-dimensional distributions of light intensity at different object distances along the detection direction can be recovered from the two-dimensional hologram. In order to verify the feasibility of this imaging scheme, we simulate the incoherent holographic imaging process of a light source with an axial length of 16 mm, and obtain the tomography light intensity distribution result with a spacing of 4 mm by reconstructing the corresponding incoherent hologram through using the backpropagation algorithms, Wiener filtering algorithm, and compress sensing algorithm. All reconstruction methods mentioned above can recover the corresponding letter light source at a certain object distance, indicating the potential of incoherent holographic technology for three-dimensional imaging. For the backpropagation reconstruction image, there is a large amount of series noise at the edge of the light source signal, which affects signal recognition in practical applications. Although the Wiener filtering algorithm can recognize the image signal to some extent, the low contrast of the reconstructed image results in the distribution of target source strength mixed with background noise. Compared with the algorithm based on the Wiener filtering and backpropagation, compress sensing theory provides a more professional technique for the ill-condition problem. Results from compress sensing reconstruction show that the crosstalk noise is significantly reduced, and the intensity distribution on the objective plane of the light source is basically concentrated in the signal area. The peak-signal-to-noise ratio of reconstructed image is continuously optimized as the number of iterations increases. Besides, the axial and horizontal resolution caused by the innermost ring radius of Fresnel zone plate are also analyzed, indicating that a shorter innermost ring radius can improve the horizontal resolution, bur reduce the axial resolution.
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Keywords:
- plasma diagnosis /
- incoherent holography /
- Fresnel zone plate /
- compress sensing
[1] Abu-Shawareb H, Acree R, Adams P, et al. (Indirect Drive ICF Collaboration) 2022 Phys. Rev. Lett. 129 075001
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Wen S H, Ding Y K 2012 Laser Inertial Confinement Fusion Diagnostics (Beijing: Arms Industry Press) p270
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Google Scholar
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Google Scholar
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Google Scholar
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Zheng Z J, Cao L F, Zhang B H, Ding Y K, Jiang S E, Li C G 2003 High Power Laser and Particle Beams 15 1001
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Cao L F 2002 Ph. D. Dissertation (Mianyang: China Academy of Engineering Physics
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图 1 非相干全息成像示意图
Figure 1. Procedure of incoherent holography.
图 2 针对微尺寸X射线源的成像示意图与二维全息图
Figure 2. Imaging system for microscale X-ray source and the corresponding 2D hologram.
图 3 模拟成像系统二维侧视图
Figure 3. 2D lateral view of the simulative imaging system.
图 4 (a)非相干全息层析重建模型; (b)基于背传输算法的重建结果; (c)基于维纳滤波算法的重建结果; (d)基于压缩感知算法的重建结果(100次迭代); (e)基于压缩感知算法的重建结果(500次迭代); (f)基于压缩感知算法的重建结果(2000次迭代)
Figure 4. (a) Tomographic reconstruction model of incoherent holography; (b) reconstruction result with backpropagate algorithms; (c) reconstruction result with Wiener filtering algorithms; (d) reconstruction result with compress sensing algorithms (100 iterations); (e) reconstruction result with compress sensing algorithms (500 iterations); (f) reconstruction result with compress sensing algorithms (2000 iterations).
图 5 PSNR与重建迭代次数间的关系
Figure 5. Relationship between PSNR and reconstruction iterations.
图 6 使用不同最内环半径波带片进行模拟成像的分辨水平对比. 在距离波带片54, 58和62 mm平面上的二维重建结果, 以及在58 mm平面内虚线标识区域的一维光强分布情况 (a) 0.08 mm; (b) 0.06 mm
Figure 6. Comparisons of resolution level in simulative imaging when applied FZP with different innermost radius. The 2D reconstruction result at the following objective depth: 54, 58 and 62 mm, and the 1D intensity distribution of the dotted line area in 58 mm plane: (a) 0.08 mm; (b) 0.06 mm.
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[1] Abu-Shawareb H, Acree R, Adams P, et al. (Indirect Drive ICF Collaboration) 2022 Phys. Rev. Lett. 129 075001
Google Scholar
[2] 温树槐, 丁永坤 2012 激光惯性约束聚变诊断学 (北京: 国防工业出版社) 第270页
Wen S H, Ding Y K 2012 Laser Inertial Confinement Fusion Diagnostics (Beijing: Arms Industry Press) p270
[3] Wang F, Jiang S E, Ding Y K, et al. 2020 Matter Radiat. Extremes 5 035201
Google Scholar
[4] Bachmann B, Hilsabeck T, Field J, et al. 2016 Rev. Sci. Instrum. 87 11e201
Google Scholar
[5] Matsuyama S, Mimura H, Yumoto H, Hara H, Yamamura K, Sano Y, Endo K, Mori Y, Yabashi M, Nishino Y, Tamasaku K, Ishikawa T, Yamauchi K 2006 Rev. Sci. Instrum. 77 093107
Google Scholar
[6] Pickworth L A, Ayers J, Bell P, et al. 2016 Rev. Sci. Instrum. 87 11e316
Google Scholar
[7] Yamada J, Matsuyama S, Sano Y, Kohmura Y, Yabashi M, Ishikawa T, Yamauchi K 2019 Opt. Express 27 3429
Google Scholar
[8] Schollmeier M S, Geissel M, Shores J E, Smith I C, Porter J L 2015 Appl. Opt. 54 5147
Google Scholar
[9] Gabor D 1948 Nature 161 777
Google Scholar
[10] Mertz L, Young N O 1961 Proceeding of the International Conference on Optical Instruments and Techniques Chapman Hall, London pp305–310
[11] Barrett H H 1972 J. Nucl. Med. 13 382
[12] Rogers W L, Jones L W, Beierwaltes W H 1973 Opt. Eng. 12 13
Google Scholar
[13] Ceglio N M, Coleman L W 1977 Phys. Rev. Lett. 39 20
Google Scholar
[14] Ceglio N M, Larsen J T 1980 Phys. Rev. Lett. 44 579
Google Scholar
[15] Caroli E, Stephen J B, Dicocco G, Natalucci L, Spizzichino A 1987 Space Sci. Rev. 45 349
Google Scholar
[16] Nakamura T, Watanabe T, Igarashi S, Chen X, Tajima K, Yamaguchi K, Shimano T, Yamaguchi M 2020 Opt. Express 28 39137
Google Scholar
[17] Shimano T, Nakamura Y, Tajima K, Sao M, Hoshizawa T 2018 Appl. Opt. 57 2841
Google Scholar
[18] Wu J C, Zhang H, Zhang W H, Jin G F, Cao L C, Barbastathis G 2020 Light: Sci. Appl. 9 53
Google Scholar
[19] Soltau J, Meyer P, Hartmann R, Strüder L, Soltau H, Salditt T 2023 Optica 10 127
Google Scholar
[20] 郑志坚, 曹磊峰, 张保汉, 丁永坤, 江少恩, 李朝光 2003 强激光与粒子束 15 1001
Zheng Z J, Cao L F, Zhang B H, Ding Y K, Jiang S E, Li C G 2003 High Power Laser and Particle Beams 15 1001
[21] 曹磊峰 2002 博士学位论文 (绵阳: 中国工程物理研究院)
Cao L F 2002 Ph. D. Dissertation (Mianyang: China Academy of Engineering Physics
[22] Brady D J, Pitsianis N, Sun X, Potuluri P 2008 US Patent US7427932 B2 [2007-07-31
[23] Romberg J 2008 IEEE Signal Process. Mag. 25 14
Google Scholar
[24] Bioucas-Dias J M, Figueiredo M A T 2007 IEEE Trans. Image Process. 16 2992
Google Scholar
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