关联成像技术中调制光场优化研究进展

宋立军, 周成, 赵希炜, 王雪

导航与控制 ›› 2020, Vol. 19 ›› Issue (1) : 48-66.

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PDF(9238 KB)
导航与控制 ›› 2020, Vol. 19 ›› Issue (1) : 48-66. DOI: 10.3969/j.issn.1674-5558.2020.01.007
量子成像与数据处理

关联成像技术中调制光场优化研究进展

  • 宋立军1,2, 周成1,2,4, 赵希炜2,3, 王雪2,3
作者信息 +

Research Progress on Modulation Light Field Optimization in Correlation Imaging

  • SONG Li-jun1,2, ZHOU Cheng1,2,4, ZHAO Xi-wei2,3, WANG Xue2,3
Author information +
文章历史 +

摘要

关联成像技术作为一种全新的成像体制,具有非局域性、抗干扰能力强、探测灵敏度高和超分辨等优点,目前已经成为研究的热点。关联成像技术的实用化进程主要受成像质量和采样效率的限制,在相同重构算法条件下,成像系统的调制光场优劣直接决定了目标物体的重构质量。在简述关联成像技术原理的基础上,重点介绍了调制光场优化的国内外研究进展,并对其发展趋势进行了展望。

Abstract

As a new imaging system, correlation imaging technology has become a hot spot of research with its non-locality, strong anti-noise ability, high detection sensitivity and super resolution. Currently, the application of correlation imaging technology is mainly restricted by the sampling efficiency and imaging quality. Under the same reconstruction algorithm, the quality of the reconstructed object is directly determined by the quality of the modulated light field of the imaging system. In this paper, based on a brief introduction to the basic principle of correlation imaging technology, the research progress of modulation light field optimization is mainly introduced, and its development trend is prospected.

关键词

关联成像 / 采样效率 / 调制光场 / 重构算法

Key words

correlation imaging / sampling efficiency / modulation light field / reconstruction algorithm

引用本文

导出引用
宋立军, 周成, 赵希炜, 王雪. 关联成像技术中调制光场优化研究进展[J]. 导航与控制, 2020, 19(1): 48-66 https://doi.org/10.3969/j.issn.1674-5558.2020.01.007
SONG Li-jun, ZHOU Cheng, ZHAO Xi-wei, WANG Xue. Research Progress on Modulation Light Field Optimization in Correlation Imaging[J]. Navigation and Control, 2020, 19(1): 48-66 https://doi.org/10.3969/j.issn.1674-5558.2020.01.007
中图分类号: O431.2   

参考文献

[1] Pittman T B, Shih Y H, Strekalov D V, et al. Optical imaging by means of two-photon quantum entanglement[J]. Physical Review A, 1995, 52(5): R3429-R3432.
[2]Strekalov D V, Sergienko A V, Klyshko D N, et al. Observation of two-photon “ghost” interference and diffra-ction[J]. Physical Review Letters, 1995, 74(18): 3600-3603.
[3]Bennink R S, Bentley S J, Boyd R W. “Two-photon” coincidence imaging with a classical source[J]. Physical Review Letters, 2002, 89(11): 113601.
[4]Gatti A, Brambilla E, Bache M, et al. Ghost imaging with thermal light: comparing entanglement and classical correlation[J]. Physical Review Letters, 2004, 93(9): 093602.
[5]Scarcelli G, Berardi V, Shih Y H. Phase-conjugate mirror via two-photon thermal light imaging[J]. Applied Physics Letters, 2006, 88(6): 061106.
[6]Zhang D, Zhai Y H, Wu L A, et al. Correlated two-photon imaging with true thermal light[J]. Optics Letters, 2005, 30(18): 2354-2356.
[7]Cheng J, Han S S. Incoherent coincidence imaging and its applicability in X-ray diffraction[J]. Physical Review Letters, 2004, 92(9): 093903.
[8]Chan W L, Charan K, Takhar D, et al. A single-pixel terahertz imaging system based on compressed sensing[J]. Applied Physics Letters, 2008, 93(12): 121105.
[9]Shapiro J H. Computational ghost imaging[J]. Physical Review A, 2008, 78(6): 061802.
[10]Bromberg Y, Katz O, Silberberg Y. Ghost imaging with a single detector[J]. Physical Review A, 2009, 79(5): 053840.
[11]邓超, 索津莉, 张志利, 等. 单像素成像中的光信息编码与解码[J]. 红外与激光工程, 2019, 48(6): 0603004.
DENG Chao, SUO Jin-li, ZHANG Zhi-li, et al. Coding and decoding of optical information in single-pixel imaging[J]. Infrared and Laser Engineering, 2019, 48(6): 0603004.
[12]李明飞, 莫小范, 张安宁. 量子成像关键技术及研究进展[J]. 导航与控制, 2016, 15(5): 1-9+16.
LI Ming-fei, MO Xiao-fan, ZHANG An-ning. The key technics in quantum imaging and its researching status[J]. Navigation and Control, 2016, 15(5): 1-9+16.
[13]吴自文, 邱晓东, 陈理想. 关联成像技术的研究现状及展望[J/OL]. http://kns.cnki.net/kcms/detail/31.1690.TN.20190508.1117.002.html.
WU Zi-wen, QIU Xiao-dong, CHEN Li-xiang. Current status and prospect for correlated imaging technique[J/OL]. http://kns.cnki.net/kcms/detail/31.1690.TN.20190508.1117.002. html.
[14]王健, 童智申, 胡晨昱, 等. 鬼成像中一些数学问题[J/OL]. http://kns.cnki.net/kcms/detail/31.1252.O4.20191120.1037.036.html.
WANG Jian, TONG Zhi-shen, HU Chen-yu, et al. Some mathematical problems in ghost imaging[J/OL]. http://kns.cnki.net/kcms/detail/31.1252.O4.20191120.1037.036.html.
[15]李恩荣, 陈明亮, 龚文林, 等. 鬼成像系统的互信息[J]. 光学学报, 2013, 33(12):1211003.
LI En-rong, CHEN Ming-liang, GONG Wen-lin, et al. Mutual information of ghost imaging systems[J]. Acta Optica Sinica, 2013, 33(12):1211003.
[16]Wang C L, Gong W L, Shao X H, et al. The influence of the property of random coded patterns on fluctuation-correlation ghost imaging[J]. Journal of Optics, 2016, 18(6): 065703.
[17]Xu X Y, Li E R, Shen X, et al. Optimization of speckle patterns in ghost imaging via sparse constraints by mutual coherence minimization[J]. Chinese Optics Letters, 2015, 13(7): 071101.
[18]Wu H, Wang C L, Gong W L, et al. Ghost imaging via sparse structured illumination source[J]. Optics Express, 2018, 26(4): 4183-4191.
[19]Hu C Y, Tong Z S, Liu Z T, et al. Optimization of light fields in ghost imaging using dictionary learning[J]. Optics Express, 2019, 27(20):28734-28749.
[20]Chen M L, Li E R, Han S S. Application of multi-correlation-scale measurement matrices in ghost imaging via sparsity constraints[J]. Applied Optics, 2014, 53(13): 2924-2928.
[21]Ma S, Hu C Y, Wang C L, et al. Multi-scale ghost imaging LiDAR via sparsity constraints using push-broom scanning[J]. Optics Communications, 2019, 448: 89-92.
[22]周成, 黄贺艳, 刘兵, 等. 基于混合散斑图的压缩计算鬼成像方法研究[J]. 光学学报, 2016, 36(9): 0911001.
ZHOU Cheng, HUANG He-yan, LIU Bing, et al. Hybrid speckle-pattern compressive computational ghost imaging[J]. Acta Optica Sinica, 2016, 36(9): 0911001.
[23]Sun S, Liu W T, Lin H Z, et al. Multi-scale adaptive computational ghost imaging[J]. Scientific Reports, 2016, 6: 37013.
[24]蔡宏吉, 姚治海, 高超, 等. 基于叠加散斑图的反射鬼成像[J].激光与光电子学进展, 2019, 56(7): 071101.
CAI Hong-ji, YAO Zhi-hai, GAO Chao, et al. Reflection ghost imaging based on superimposed speckle-pattern[J]. Laser & Optoelectronics Progress, 2019, 56(7): 071101.
[25]Wang X X, Tao Y, Yang F B, et al. An effective compressive computational ghost imaging with hybrid speckle pattern[J]. Optics Communications, 2020, 454: 124470.
[26]冯维, 赵晓冬, 汤少靖, 等. 基于区域分割的压缩计算鬼成像方法研究[J/OL]. http://kns.cnki.net/kcms/detail/31.1690.TN.20191106.1205.066.html.
FENG Wei, ZHAO Xiao-dong, TANG Shao-jing, et al. Compressive computational ghost imaging method based on region segmentation[J/OL]. http://kns.cnki.net/kcms/detail/ 31.1690.TN.20191106.1205.066.html.
[27]Olivas S J, Rachlin Y, Gu L, et al. Characterization of a compressive imaging system using laboratory and natural light scenes[J]. Applied Optics, 2013, 52(19): 4515-4526.
[28]Phillips B D, Sun M J, Taylor J M, et al. Adaptive foveated single-pixel imaging with dynamic supersampling[J]. Science Advances, 2017, 3(4): e1601782.
[29]Sun M J, Meng L T, Edgar M P, et al. A Russian dolls ordering of the Hadamard basis for compressive single-pixel imaging[J]. Scientific Reports, 2017, 7(1): 3464.
[30]李明飞, 莫小范, 赵连洁, 等. 基于Walsh-Hadamard变换的单像素遥感成像[J]. 物理学报, 2016, 65(6): 064201.
LI Ming-fei, MO Xiao-fan, ZHAO Lian-jie, et al. Single-pixel remote imaging based on Walsh-Hadamard transform[J]. Acta Physica Sinica, 2016, 65(6): 064201.
[31]李明飞, 阎璐, 杨然, 等. 基于Hadamard矩阵优化排序的快速单像素成像[J]. 物理学报, 2019, 68(6): 064202.
LI Ming-fei, YAN Lu, YANG Ran, et al. Fast single-pixel imaging based on optimized reordering Hadamard basis[J]. Acta Physica Sinica, 2019, 68(6): 064202.
[32]Yu W K, Liu Y M. Single-pixel imaging with origami pattern construction[J]. Sensors, 2019, 19(23): 5135.
[33]Yu W K. Super sub-Nyquist single-pixel imaging by means of cake-cutting Hadamard basis sort[J]. Sensors, 2019, 19(19): 4122.
[34]Zhou C, Tian T, Gao C, et al. Multi-resolution progre-ssive computational ghost imaging[J]. Journal of Optics, 2019, 21(5): 055702.
[35]Ma H Y, Sang A J, Zhou C, et al. A zigzag scanning ordering of four-dimensional Walsh basis for single-pixel imaging[J]. Optics Communications, 2019, 443: 69-75.
[36]Zhou C, Yu X, Zhao X W, et al. Hadamard ‘pipeline’ coding computational ghost imaging [J/OL]. https://arxiv.org/pdf/1910.06731v1.pdf.
[37]Zhao X W, Wang X, Zhang W Y, et al. Gold matrix ghost Imaging[J/OL]. https://arxiv.org/pdf/1911.05451v1.pdf.
[38]Ye Z Y, Wang H B, Xiong J, et al. Simultaneous full-color single-pixel imaging and visible watermarking using Hadamard-Bayer illumination patterns[J]. Optics and Lasers in Engineering, 2020, 127: 105955.
[39]张伟良, 张闻文, 何睿清, 等. 基于局部Hadamard 调制的迭代去噪鬼成像[J]. 光学学报, 2016, 36(4): 0411001.
ZHANG Wei-liang, ZHANG Wen-wen, HE Rui-qing, et al. Iterative denoising ghost imaging based on local Hadamard modulation[J]. Acta Optica Sinica, 2016, 36(4): 0411001.
[40]Wu H, Wang R Z, Li C S, et al. Influence of intensity fluctuations on Hadamard-based computational ghost imaging[J]. Optics Communications, 2020, 454: 124490.
[41]Khamoushi S M M, Nosrati Y, Tavassoli S H, et al. Sinusoidal ghost imaging[J]. Optics Letters, 2015, 40(15): 3452-3455.
[42]Zhang Z B, Ma X, Zhong J G. Single-pixel imaging by means of Fourier spectrum acquisition [J]. Nature Communications, 2015, 6: 6225.
[43]Huang J, Shi D F, Yuan K, et al. Computational-weighted Fourier single-pixel imaging via binary illumination[J]. Optics Express, 2018, 26:16547-16559.
[44]Czajkowski K M, Pastuszczak A, Kotyński R. Real-time single-pixel video imaging with Fourier domain regularization[J]. Optics Express, 2018, 26: 20009-20022.
[45]Zhang Z B, Wang X Y, Zheng G A, et al. Fast Fourier single-pixel imaging via binary illumination[J]. Scientific Reports, 2017, 7(1): 12029.
[46]Zhang Z B, Wang X Y, Zheng G A, et al. Hadamard single-pixel imaging versus Fourier single-pixel imaging[J]. Optics Express, 2017, 25(16): 19619-19639.
[47]Zhang Z B, Ye J Q, Deng Q W, et al. Image-free real-time detection and tracking of fast moving object using a single-pixel detector[J]. Optics Express, 2019, 27(24): 35394-35401.
[48]张子邦, 陆天傲, 彭军政, 等. 傅里叶单像素成像技术与应用[J]. 红外与激光工程, 2019, 48(6): 603002.
ZHANG Zi-bang, LU Tian-ao, PENG Jun-zheng, et al. Fourier single-pixel imaging techniques and applications[J]. Infrared and Laser Engineering, 2019, 48(6): 603002.
[49]Ye Z Y, Qiu P H, Wang H B, et al. Image watermarking and fusion based on Fourier single-pixel imaging with weighed light source[J]. Optics Express, 2019, 27(25): 36505-36523.
[50]Liu B L, Yang Z H, Liu X, et al. Coloured computational imaging with single-pixel detectors based on a 2D discrete cosine transform[J]. Journal of Modern Optics, 2017, 64(3): 259-264.
[51]Jiang H Z, Zhai H J, Xu Y, et al. 3D shape measurement of translucent objects based on Fourier single-pixel imaging in projector-camera system[J]. Optics Express, 2019, 27(23): 33564-33574.
[52]曹非, 郑素赢, 赵生妹, 等. 正交散斑鬼成像[J]. 信号处理, 2019, 35(5): 781-785.
CAO Fei, ZHENG Su-ying, ZHAO Sheng-mei, et al. Orthogonal speckle ghost imaging[J]. Journal of Signal Processing, 2019, 35(5): 781-785.
[53]Chen Y, Liu S, Yao X R, et al. Discrete cosine single-pixel microscopic compressive imaging via fast binary modulation[J]. Optics Communications, 2020, 454: 124512.
[54]龚文林, 王成龙, 梅笑冬, 等. 面向实际应用的GISC Lidar近期研究进展与思考[J]. 红外与激光工程, 2018, 47(3): 0302001.
GONG Wen-lin, WANG Cheng-long, MEI Xiao-dong, et al. Recent research progress and thoughts on GISC Lidar with respect to practical applications[J]. Infrared and Laser Engineering, 2018, 47(3): 0302001.
[55]梅笑冬, 龚文林, 严毅, 等. 可预置强度关联激光三维成像雷达实验研究[J]. 中国激光, 2016, 43(7): 0710003.
MEI Xiao-dong, GONG Wen-lin, YAN Yi, et al. Experimental research on prebuilt three-dimensional imaging lidar[J]. Chinese Journal of Lasers, 2016, 43(7): 0710003.
[56]Kittle D, Choi K, Wagadarikar A, et al. Multiframe image estimation for coded aperture snapshot spectral imagers[J]. Applied Optics, 2010, 49(36): 6824-6833.
[57]张成, 杨海蓉, 韦穗. 循环托普利兹块相位掩模可压缩双透镜成像[J]. 光学学报, 2011, 31(8): 0811001.
ZHANG Cheng, YANG Hai-rong, WEI Sui. Compressive double-lens imaging using circulant-Toeplitz-block phase mask[J]. Acta Optica Sinica, 2011, 31(8): 0811001.
[58]Liu Z T, Tan S Y, Wu J R, et al. Spectral camera based on ghost imaging via sparsity constraints[J]. Scientific Reports, 2016, 6: 25718.
[59]Wu J R, Li E R, Shen X, et al. Experimental results of the balloon-borne spectral camera based on ghost imaging via sparsity constraints[J]. IEEE Access, 2018, 6: 68740-68748.
[60]Li W W, Tong Z S, Xiao K, et al. Single frame wide-field nanoscopy based on ghost imaging via sparsity constraints[J]. Optica, 2019, 6(12): 1515-1523.
[61]Pelliccia D, Rack A, Scheel M, et al. Experimental x-ray ghost imaging[J]. Physical Review Letters, 2016, 117(11): 113902.
[62]Yu H, Lu R H, Han S S, et al. Fourier-transform ghost imaging with hard X rays[J]. Physical Review Letters, 2016, 117(11): 113901.
[63]赵鑫, 喻虹, 陆荣华, 等. X光傅里叶变换关联成像赝热光源研究[J]. 光学学报, 2017, 37(5): 0511001.
ZHAO Xin, YU Hong, LU Rong-hua, et al. Research on pseudo-thermal source of X-ray Fourier-transform ghost imaging[J]. Acta Optica Sinica, 2017, 37(5): 0511001.
[64]Yu H, Lu R H, Tan Z J, et al. Recent progress in x-ray Fourier-transform ghost imaging[J]. Nuclear Instruments and Methods in Physics Research Section A: Acceler-ators, Spectrometers, Detectors and Associated Equip-ment, 2019, 928(4): 33-36.
[65]Zhang A X, He Y H, Wu L A, et al.Tabletop x-ray ghost imaging with ultra-low radiation[J]. Optica, 2018, 5(4) : 374-377.
[66]Song L J, Zhou C, Chen L, et al. Demonstration of single pixel computational ghost imaging with pseudo-randomly patterned illumination from a liquid crystal display[C]. Proceedings of the SPIE, 2016, 10141: 101411G.
[67]Onose S, Takahashi M, Mizutani Y, et al. Single pixel imaging with a high-frame-rate LED array[C]. JSAP-OSA Joint Symposia, 2016: 04-011.
[68]Xu Z H, Chen W, Penuelas J, et al. 1000 fps computational ghost imaging using LED-based structured illumination[J]. Optics Express, 2018, 26(3): 2427-2434.
[69]Zhao W G, Chen H, Yuan Y, et al. Ultrahigh-speed color imaging with single-pixel detectors under low light level[J]. Physical Review Applied, 2019, 12(3): 034049.
[70]Nitta K, Yano Y, Kitada C, et al. Fast computational ghost imaging with laser array modulation[J]. Applied Sciences, 2019, 9(22): 4807.
[71]Liu C B, Chen J Q, Liu J X, et al. High frame-rate computational ghost imaging system using an optical fiber phased array and a low-pixel APD array[J]. Optics Express, 2018, 26(8): 10048-10064.
[72]Fukui T, Nakano Y, Tanemura T. On ghost imaging using multimode fiber and integrated optical phased array[C]. 24th Opto-Electronics and Communications Confer-ence and International Conference on Photonics in Switching and Computing, 2019: 1-3.
[73]Niu Z Z, Shi J H, Sun L, et al. Photon-limited face image super-resolution based on deep learning[J]. Optics Express, 2018, 26(18):22773-22782.
[74]Sun Y W, Shi J H, Sun L, et al. Image reconstruction through dynamic scattering media based on deep learning[J]. Optics Express, 2019, 27(11):16032-16046.
[75]王飞, 王昊, 卞耀明, 等. 深度学习在计算成像中的应用[J]. 光学学报, 2020, 40(1): 0111002.
WANG Fei, WANG Hao, BIAN Yao-ming, et al. Applications of deep learning in computational imaging[J]. Acta Optica Sinica, 2020, 40(1): 0111002.
[76]Aβmann M, Bayer M. Compressive adaptive computa-tional ghost imaging[J]. Scientific Reports, 2013, 3: 11545.
[77]Yu W K, Li M F, Yao X R, et al. Adaptive compressive ghost imaging based on wavelet trees and sparse representation[J]. Optics Express, 2014, 22(6):7133-7144.
[78]Xi M J, Chen H, Yuan Y, et al. Bi-frequency 3D ghost imaging with Haar wavelet transform[J]. Optics Express, 2019, 27(22):32349-32359.

基金

吉林省产业自主创新能力项目(编号:2018C040-4,2019C025)
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