留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

傅里叶单像素成像技术与应用

张子邦 陆天傲 彭军政 钟金钢

张子邦, 陆天傲, 彭军政, 钟金钢. 傅里叶单像素成像技术与应用[J]. 红外与激光工程, 2019, 48(6): 603002-0603002(19). doi: 10.3788/IRLA201948.0603002
引用本文: 张子邦, 陆天傲, 彭军政, 钟金钢. 傅里叶单像素成像技术与应用[J]. 红外与激光工程, 2019, 48(6): 603002-0603002(19). doi: 10.3788/IRLA201948.0603002
Zhang Zibang, Lu Tian'ao, Peng Junzheng, Zhong Jingang. Fourier single-pixel imaging techniques and applications[J]. Infrared and Laser Engineering, 2019, 48(6): 603002-0603002(19). doi: 10.3788/IRLA201948.0603002
Citation: Zhang Zibang, Lu Tian'ao, Peng Junzheng, Zhong Jingang. Fourier single-pixel imaging techniques and applications[J]. Infrared and Laser Engineering, 2019, 48(6): 603002-0603002(19). doi: 10.3788/IRLA201948.0603002

傅里叶单像素成像技术与应用

doi: 10.3788/IRLA201948.0603002
基金项目: 

国家自然科学基金(61875074,61475064);暨南大学科研培育与创新基金(11618307)

详细信息
    作者简介:

    张子邦(1988-),男,副教授,硕士生导师,博士,主要从事单像素成像与显微计算成像等方面的研究。Email:charles.cheung.zzb@gmail.com

    通讯作者: 钟金钢(1964-),男,教授,博士生导师,博士,主要从事光学工程与生物医学光学等方面的研究。Email:tzjg@jnu.edu.cn
  • 中图分类号: O439

Fourier single-pixel imaging techniques and applications

  • 摘要: 非可见光成像是光学成像领域中的难题之一。单像素成像作为一种新型的计算成像技术,利用空间光调制技术,可实现只使用一个无空间分辨能力的单像素探测器获取物体的空间信息。因此单像素成像是解决传统成像在非可见光波段成像难题的潜在解决方案之一。近年,傅里叶单像素成像技术被证明是一种可以兼得高成像质量和高成像效率的单像素成像技术。自2015年被提出至今,傅里叶单像素成像已经从二维成像推广到三维成像、从灰度成像推广到彩色成像、从静态成像推广到动态成像、从单模态成像推广到多模态成像、从宏观成像推广到显微成像,发展出一系列的成像技术。对傅里叶单像素成像技术的基本原理、与之相关的成像技术和应用进行了综述,并讨论了现存的一些关键问题以及今后可能的研究方向。
  • [1] Butler P D, Silverstein S M, Dakin S C. Visual perception and its impairment in schizophrenia[J]. Biological Psychiatry, 2008, 64(1):40-47.
    [2] Nakano A. Spinning-disk confocal microscopy-a cutting-edge tool for imaging of membrane traffic[J]. Cell Structure and Function, 2002, 27(5):349-355.
    [3] Duarte M F, Davenport M A, Takhar D, et al. Single-pixel imaging via compressive sampling[J]. IEEE Signal Processing Magazine, 2008, 25(2):83-91.
    [4] Welsh S S, Edgar M P, Bowman R, et al. Fast full-color computational imaging with single-pixel detectors[J]. Optics Express, 2013, 21(20):23068-23074.
    [5] Bian L, Suo J, Situ G, et al. Multispectral imaging using a single bucket detector[J]. Scientific Reports, 2016, 6:24752.
    [6] Rousset F, Ducros N, Peyrin F, et al. Time-resolved multispectral imaging based on an adaptive single-pixel camera[J]. Optics Express, 2018, 26(8):10550-10558.
    [7] Zhang Z, Liu S, Peng J, et al. Simultaneous spatial, spectral, and 3D compressive imaging via efficient Fourier single-pixel measurements[J]. Optica, 2018, 5(3):315-319.
    [8] Studer V, Bobin J, Chahid M, et al. Compressive fluorescence microscopy for biological and hyperspectral imaging[J]. Proceedings of the National Academy of Sciences, 2012, 109(26):E1679-E1687.
    [9] Hahn J, Debes C, Leigsnering M, et al. Compressive sensing and adaptive direct sampling in hyperspectral imaging[J]. Digital Signal Processing, 2014, 26:113-126.
    [10] Edgar M P, Gibson G M, Bowman R W, et al. Simultaneous real-time visible and infrared video with single-pixel detectors[J]. Scientific Reports, 2015, 5:10669.
    [11] 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.
    [12] Watts C M, Shrekenhamer D, Montoya J, et al. Terahertz compressive imaging with metamaterial spatial light modulators[J]. Nature Photonics, 2014, 8(8):605.
    [13] Stantchev R I, Sun B, Hornett S M, et al. Noninvasive, near-field terahertz imaging of hidden objects using a single-pixel detector[J]. Science Advances, 2016, 2(6):e1600190.
    [14] Gibson G M, Sun B, Edgar M P, et al. Real-time imaging of methane gas leaks using a single-pixel camera[J]. Optics Express, 2017, 25(4):2998-3005.
    [15] Radwell N, Mitchell K J, Gibson G M, et al. Single-pixel infrared and visible microscope[J]. Optica, 2014, 1(5):285-289.
    [16] Zhang Y, Edgar M P, Sun B, et al. 3D single-pixel video[J]. Journal of Optics, 2016, 18(3):035203.
    [17] Goldstein T, Xu L, Kelly K F, et al. The stone transform:Multi-resolution image enhancement and compressive video[J]. IEEE Transactions on Image Processing, 2015, 24(12):5581-5593.
    [18] Zhang Z, Wang X, Zheng G, et al. Fast Fourier single-pixel imaging via binary illumination[J]. Scientific Reports, 2017, 7(1):12029.
    [19] Higham C F, Murray-Smith R, Padgett M J, et al. Deep learning for real-time single-pixel video[J]. Scientific Reports, 2018, 8(1):2369.
    [20] Zheng J, Jacobs E L. Video compressive sensing using spatial domain sparsity[J]. Optical Engineering, 2009, 48(8):087006.
    [21] Sankaranarayanan A C, Xu L, Studer C, et al. Video compressive sensing for spatial multiplexing cameras using motion-flow models[J]. SIAM Journal on Imaging Sciences, 2015, 8(3):1489-1518.
    [22] Xu L, Sankaranarayanan A, Studer C, et al. Multiscale compressive video acquisition[C]//Computational Optical Sensing and Imaging. Optical Society of America, 2013:CW2C. 4.
    [23] Wu Y, Ye P, Mirza I O, et al. Experimental demonstration of an optical-sectioning compressive sensing microscope (CSM)[J]. Optics Express, 2010, 18(24):24565-24578.
    [24] Sun B, Edgar M P, Bowman R, et al. 3D computational imaging with single-pixel detectors[J]. Science, 2013, 340(6134):844-847.
    [25] Howland G A, Dixon P B, Howell J C. Photon-counting compressive sensing laser radar for 3D imaging[J]. Applied Optics, 2011, 50(31):5917-5920.
    [26] Howland G A, Lum D J, Ware M R, et al. Photon counting compressive depth mapping[J]. Optics Express, 2013, 21(20):23822-23837.
    [27] Sun M J, Edgar M P, Phillips D B, et al. Improving the signal-to-noise ratio of single-pixel imaging using digital microscanning[J]. Optics Express, 2016, 24(10):10476-10485.
    [28] Edgar M P, Sun M J, Gibson G M, et al. Real-time 3D video utilizing a compressed sensing time-of-flight single-pixel camera[C]//Optical Trapping and Optical Micromanipulation XⅢ. International Society for Optics and Photonics, 2016, 9922:99221B.
    [29] Zhang Z, Zhong J. Three-dimensional single-pixel imaging with far fewer measurements than effective image pixels[J]. Optics Letters, 2016, 41(11):2497-2500.
    [30] Durn V, Clemente P, Fernndez-Alonso M, et al. Single-pixel polarimetric imaging[J]. Optics Letters, 2012, 37(5):824-826.
    [31] Soldevila F, Irles E, Durn V, et al. Single-pixel polarimetric imaging spectrometer by compressive sensing[J]. Applied Physics B, 2013, 113(4):551-558.
    [32] Welsh S S, Edgar M P, Bowman R, et al. Near video-rate linear Stokes imaging with single-pixel detectors[J]. Journal of Optics, 2015, 17(2):025705.
    [33] Tajahuerce E, Durn V, Clemente P, et al. Image transmission through dynamic scattering media by single-pixel photodetection[J]. Optics Express, 2014, 22(14):16945-16955.
    [34] Durn V, Soldevila F, Irles E, et al. Compressive imaging in scattering media[J]. Optics Express, 2015, 23(11):14424-14433.
    [35] Greenberg J, Krishnamurthy K, Brady D. Compressive single-pixel snapshot x-ray diffraction imaging[J]. Optics Letters, 2014, 39(1):111-114.
    [36] Huynh N, Zhang E, Betcke M, et al. Single-pixel optical camera for video rate ultrasonic imaging[J]. Optica, 2016, 3(1):26-29.
    [37] Yang J, Gong L, Xu X, et al. Motionless volumetric photoacoustic microscopy with spatially invariant resolution[J]. Nature Communications, 2017, 8(1):780.
    [38] Clemente P, Durn V, Tajahuerce E, et al. Compressive holography with a single-pixel detector[J]. Optics Letters, 2013, 38(14):2524-2527.
    [39] Soldevila F, Durn V, Clemente P, et al. Phase imaging by spatial wavefront sampling[J]. Optica, 2018, 5(2):164-174.
    [40] Lochocki B, Gambn A, Manzanera S, et al. Single pixel camera ophthalmoscope[J]. Optica, 2016, 3(10):1056-1059.
    [41] Ota S, Horisaki R, Kawamura Y, et al. Ghost cytometry[J]. Science, 2018, 360(6394):1246-1251.
    [42] Guo Q, Chen H, Weng Z, et al. Compressive sensing based high-speed time-stretch optical microscopy for two-dimensional image acquisition[J]. Optics Express, 2015, 23(23):29639-29646.
    [43] 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.
    [44] Yu W K, Liu X F, Yao X R, et al. Complementary compressive imaging for the telescopic system[J]. Scientific Reports, 2014, 4:5834.
    [45] Gong W, Zhao C, Yu H, et al. Three-dimensional ghost imaging lidar via sparsity constraint[J]. Scientific Reports, 2016, 6:26133.
    [46] Katz O, Bromberg Y, Silberberg Y. Compressive ghost imaging[J]. Applied Physics Letters, 2009, 95(13):131110.
    [47] Donoho D L. Compressed sensing[J]. IEEE Transactions on Information Theory, 2006, 52(4):1289-1306.
    [48] Sun M J, Edgar M P, Gibson G M, et al. Single-pixel three-dimensional imaging with time-based depth resolution[J]. Nature Communications, 2016, 7:12010.
    [49] 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.
    [50] 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.
    [51] Salvador-Balaguer E, Latorre-Carmona P, Chabert C, et al. Low-cost single-pixel 3D imaging by using an LED array[J]. Optics Express, 2018, 26(12):15623-15631.
    [52] Durn V, Clemente P, Fernndez-Alonso M, et al. Single-pixel polarimetric imaging[J]. Optics Letters, 2012, 37(5):824-826.
    [53] Zhang Z, Jiao S, Yao M, et al. Secured single-pixel broadcast imaging[J]. Optics Express, 2018, 26(11):14578-14591.
    [54] Zhang Z, Su Z, Deng Q, et al. Lensless single-pixel imaging by using LCD:application to small-size and multi-functional scanner[J]. Optics Express, 2019, 27(3):3731-3745.
    [55] 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.
    [56] Rousset F, Ducros N, Farina A, et al. Adaptive basis scan by wavelet prediction for single-pixel imaging[J]. IEEE Transactions on Computational Imaging, 2017, 3(1):36-46.
    [57] Zhang Z, Ma X, Zhong J. Single-pixel imaging by means of Fourier spectrum acquisition[J]. Nature Communications, 2015, 6:6225.
    [58] Peng J, Yao M, Cheng J, et al. Micro-tomography via single-pixel imaging[J]. Opt Express, 2018, 26(24):31094-31105.
    [59] Zhang Z, Wang X, Zheng G, et al. Hadamard single-pixel imaging versus Fourier single-pixel imaging[J]. Optics Express, 2017, 25(16):19619-19639.
    [60] Mitra S K, Kuo Y. Digital Signal Processing:a Computer-Based Approach[M]. New York:McGraw-Hill, 2006.
    [61] Floyd R W. An adaptive algorithm for spatial gray-scale[C]//Proceedings of the Society for Information Display, 1976, 17:75-77.
    [62] Takeda M, Mutoh K. Fourier transform profilometry for the automatic measurement of 3-D object shapes[J]. Applied Optics, 1983, 22(24):3977-3982.
    [63] Born M, Wolf E. Principles of Optics:Electromagnetic Theory of Propagation, Interference and Diffraction of Light[M]. Berlin:Elsevier, 1980.
    [64] Longere P, Zhang X, Delahunt P B, et al. Perceptual assessment of demosaicing algorithm performance[J]. Proceedings of the IEEE, 2002, 90(1):123-132.
    [65] Malvar H S, He L-W, Cutler R. High-quality linear interpolation for demosaicing of Bayer-patterned color images[C]//2004 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2004:iii-485.
    [66] Jiang H, Liu Y, Li X, et al. Point spread function measurement based on single-pixel imaging[J]. IEEE Photonics Journal, 2018, 10(6):1-15.
    [67] Chen H, Shi J, Liu X, et al. Single-pixel non-imaging object recognition by means of Fourier spectrum acquisition[J]. Optics Communications, 2018, 413:269-275.
    [68] Zheng G, Kolner C, Yang C. Microscopy refocusing and dark-field imaging by using a simple LED array[J]. Optics Letters, 2011, 36(20):3987-3989.
    [69] Tian L, Wang J, Waller L. 3D differential phase-contrast microscopy with computational illumination using an LED array[J]. Optics Letters, 2014, 39(5):1326-1329.
    [70] Zhang Z, Yao M, Li X, et al. Simultaneous functional and structural imaging for photovoltaic devices[J]. Solar Energy Materials and Solar Cells, 2019, 193:101-106.
    [71] Li S, Zhang Z, Ma X, et al. Shadow-free single-pixel imaging[J]. Optics Communications, 2017, 403:257-261.
    [72] Sun M J, Huang J Y, Penuelas J. Suppressing the noise in binarized Fourier single-pixel imaging utilizing defocus blur[J]. Optics and Lasers in Engineering, 2018, 108:15-18.
    [73] Zhang Y, Suo J, Wang Y, et al. Doubling the pixel count limitation of single-pixel imaging via sinusoidal amplitude modulation[J]. Optics Express, 2018, 26(6):6929-6942.
    [74] Khamoushi S M M, Tavassoli S H. Apodized Fourier single-pixel imaging by changing the contrast of patterns using Norton-Beer functions[J]. Journal of Optics, 2019, 21(2):025702.
    [75] Bian L, Suo J, Hu X, et al. Efficient single pixel imaging in Fourier space[J]. Journal of Optics, 2016, 18(8):085704.
    [76] Xu B, Jiang H, Zhao H, et al. Projector-defocusing rectification for Fourier single-pixel imaging[J]. Optics Express, 2018, 26(4):5005-5017.
    [77] Jiang H, Liu H, Li X, et al. Efficient regional single-pixel imaging for multiple objects based on projective reconstruction theorem[J]. Optics and Lasers in Engineering, 2018, 110:33-40.
    [78] Huang J, Shi D, Yuan K, et al. Computational-weighted Fourier single-pixel imaging via binary illumination[J]. Optics Express, 2018, 26(13):16547-16559.
    [79] Xiao Y, Zhou L, Chen W. Fourier spectrum retrieval in single-pixel imaging[J]. IEEE Photonics Journal, 2019, 11(2):1-11.
  • [1] 杨旭, 冉悦, 周伟, 徐宝腾, 刘家林, 杨西斌.  全彩单像素内窥成像系统 . 红外与激光工程, 2023, 52(10): 20230077-1-20230077-8. doi: 10.3788/IRLA20230077
    [2] 左超, 陈钱.  计算光学成像:何来,何处,何去,何从? . 红外与激光工程, 2022, 51(2): 20220110-1-20220110-184. doi: 10.3788/IRLA20220110
    [3] 赵海博, 刘彦丽, 杨雯铄, 苏云, 高大化, 孙权森, 赵慧洁.  双通道衍射计算成像光谱仪系统 . 红外与激光工程, 2022, 51(5): 20220077-1-20220077-8. doi: 10.3788/IRLA20220077
    [4] 陆秋萍, 石岩, 戴晟昕, 陈义, 赵春柳, 赵天琦, 金尚忠, 牛海彬.  生物组织单像素成像重构的散射干扰抑制 . 红外与激光工程, 2022, 51(3): 20210722-1-20210722-7. doi: 10.3788/IRLA20210722
    [5] 翟鑫亮, 吴晓燕, 孙艺玮, 石剑虹, 曾贵华.  单像素成像理论与方法(特邀) . 红外与激光工程, 2021, 50(12): 20211061-1-20211061-14. doi: 10.3788/IRLA20211061
    [6] 刘瑞丰, 赵书朋, 李福利.  单像素复振幅成像(特邀) . 红外与激光工程, 2021, 50(12): 20210735-1-20210735-16. doi: 10.3788/IRLA20210735
    [7] 程永强, 王宏强, 曹凯程, 刘康, 罗成高.  微波关联成像研究进展及展望(特邀) . 红外与激光工程, 2021, 50(12): 20210790-1-20210790-21. doi: 10.3788/IRLA20210790
    [8] 郑培霞, 刘亦辰, 刘宏超.  单像素成像与超表面成像(特邀) . 红外与激光工程, 2021, 50(12): 20211058-1-20211058-12. doi: 10.3788/IRLA20211058
    [9] 廖兆琨, 王汉, 陈文, 孙鸣捷.  紧凑双光路单像素成像系统(特邀) . 红外与激光工程, 2021, 50(12): 20210723-1-20210723-7. doi: 10.3788/IRLA20210723
    [10] 范斌, 刘彦丽, 赵海博, 徐婧, 孙权森, 王旭.  新型深空高光谱衍射计算成像探测技术(特约) . 红外与激光工程, 2020, 49(5): 20201005-20201005-6. doi:  10.3788.IRLA20201005
    [11] 石峰, 陆同希, 杨书宁, 苗壮, 杨晔, 张闻文, 何睿清.  噪声环境下基于单像素成像系统和深度学习的目标识别方法 . 红外与激光工程, 2020, 49(6): 20200010-1-20200010-8. doi: 10.3788/IRLA20200010
    [12] 姜宏志, 李宇曦, 赵慧洁.  单像素成像在三维测量中的应用 . 红外与激光工程, 2020, 49(3): 0303017-0303017-9. doi: 10.3788/IRLA202049.0303017
    [13] 孙宝清, 江山, 马艳洋, 蒋文杰, 殷永凯.  单像素成像在特殊波段及三维成像的应用发展 . 红外与激光工程, 2020, 49(3): 0303016-0303016-16. doi: 10.3788/IRLA202049.0303016
    [14] 刘正君, 耿勇, 谭久彬.  基于柱透镜多旋转测量的计算成像 . 红外与激光工程, 2019, 48(6): 603016-0603016(5). doi: 10.3788/IRLA201948.0603016
    [15] 李明飞, 阚宝玺, 霍娟, 阎璐, 刘院省.  水平大气环境34 km单像素成像实验 . 红外与激光工程, 2019, 48(9): 925002-0925002(6). doi: 10.3788/IRLA201948.0925002
    [16] 孙鸣捷, 张佳敏.  单像素成像及其在三维重建中的应用 . 红外与激光工程, 2019, 48(6): 603003-0603003(11). doi: 10.3788/IRLA201948.0603003
    [17] 邓超, 索津莉, 张志利, 戴琼海.  单像素成像中的光信息编码与解码 . 红外与激光工程, 2019, 48(6): 603004-0603004(11). doi: 10.3788/IRLA201948.0603004
    [18] 李亚鹏, 何斌, 付天骄.  行间转移型面阵CCD成像系统设计 . 红外与激光工程, 2014, 43(8): 2602-2606.
    [19] 陈超, 杨鸿儒, 吴磊, 俞兵, 袁良, 杨斌, 黎高平.  距离选通成像系统关键性能的实验 . 红外与激光工程, 2013, 42(12): 3423-3427.
    [20] 葛卫龙, 华良洪, 张晓晖.  距离选通水下激光成像系统信噪比分析与计算 . 红外与激光工程, 2013, 42(8): 2022-2026.
  • 加载中
计量
  • 文章访问数:  1329
  • HTML全文浏览量:  197
  • PDF下载量:  435
  • 被引次数: 0
出版历程
  • 收稿日期:  2019-01-05
  • 修回日期:  2019-02-03
  • 刊出日期:  2019-06-25

傅里叶单像素成像技术与应用

doi: 10.3788/IRLA201948.0603002
    作者简介:

    张子邦(1988-),男,副教授,硕士生导师,博士,主要从事单像素成像与显微计算成像等方面的研究。Email:charles.cheung.zzb@gmail.com

    通讯作者: 钟金钢(1964-),男,教授,博士生导师,博士,主要从事光学工程与生物医学光学等方面的研究。Email:tzjg@jnu.edu.cn
基金项目:

国家自然科学基金(61875074,61475064);暨南大学科研培育与创新基金(11618307)

  • 中图分类号: O439

摘要: 非可见光成像是光学成像领域中的难题之一。单像素成像作为一种新型的计算成像技术,利用空间光调制技术,可实现只使用一个无空间分辨能力的单像素探测器获取物体的空间信息。因此单像素成像是解决传统成像在非可见光波段成像难题的潜在解决方案之一。近年,傅里叶单像素成像技术被证明是一种可以兼得高成像质量和高成像效率的单像素成像技术。自2015年被提出至今,傅里叶单像素成像已经从二维成像推广到三维成像、从灰度成像推广到彩色成像、从静态成像推广到动态成像、从单模态成像推广到多模态成像、从宏观成像推广到显微成像,发展出一系列的成像技术。对傅里叶单像素成像技术的基本原理、与之相关的成像技术和应用进行了综述,并讨论了现存的一些关键问题以及今后可能的研究方向。

English Abstract

参考文献 (79)

目录

    /

    返回文章
    返回