Abstract
With the development of computer science, more and more hardware implementations can be reproduced by software programming, bringing compact, cheap, and fast components to imaging instrumentation. In recent years, computational methods have been introduced into spectral detection, and computational spectrum acquisition implementations have emerged. This paper highlights the advantages of computational spectrum acquisition implementations by comparing them with traditional non-computational methods. Then, focusing on the compact feature, we review the most representative implementations, and finally make discussion and offer an outlook.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Adato R, Yanik AA, Amsden JJ, et al., 2009. Ultra-sensitive vibrational spectroscopy of protein monolayers with plasmonic nanoantenna arrays. PNAS, 106(46):19227–19232. https://doi.org/10.1073/pnas.0907459106
Arguello H, Arce GR, 2011. Code aperture optimization for spectrally agile compressive imaging. J Opt Soc Am A, 28(11):2400–2413. https://doi.org/10.1364/josaa.28.002400
Arguello H, Arce GR, 2014. Colored coded aperture design by concentration of measure in compressive spectral imaging. IEEE Trans Image Process, 23(4):1896–1908. https://doi.org/10.1109/tip.2014.2310125
Arguello H, Correa CV, Arce GR, 2013. Fast lapped block reconstructions in compressive spectral imaging. Appl Opt, 52(10):D32–D45. https://doi.org/10.1364/ao.52.000d32
Bangalore AS, Shaffer RE, Small GW, et al., 1996. Genetic algorithm-based method for selecting wavelengths and model size for use with partial least-squares regression: application to near-infrared spectroscopy. Anal Chem, 68(23):4200–4212. https://doi.org/10.1021/ac9607121
Bao J, Bawendi MG, 2015. A colloidal quantum dot spectrometer. Nature, 523(7558):67–70. https://doi.org/10.1038/nature14576
Baraniuk RG, 2007. Compressive sensing. IEEE Signal Process Mag, 24(4):118–121. https://doi.org/10.1109/msp.2007.4286571
Bulygin TV, Vishnyakov GN, 1992. Spectrotomography: a new method of obtaining spectrograms of two-dimensional objects. Analytical Methods for Optical Tomography, p.315–323. https://doi.org/10.1117/12.131904
Candès EJ, Wakin MB, 2008. An introduction to compressive sampling. IEEE Signal Process Mag, 25(2):21–30. https://doi.org/10.1109/msp.2007.914731
Candès EJ, Romberg J, Tao T, 2006. Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information. IEEE Trans Inform Theory, 52(2):489–509. https://doi.org/10.1109/tit.2005.862083
Chaganti K, Salakhutdinov I, Avrutsky I, et al., 2006. A simple miniature optical spectrometer with a planar waveguide grating coupler in combination with a plano-convex lens. Opt Expr, 14(9):4064–4072. https://doi.org/10.1364/oe.14.004064
Chang CC, Lee HN, 2008. On the estimation of target spectrum for filter-array based spectrometers. Opt Expr, 16(2):1056–1061. https://doi.org/10.1364/oe.16.001056
Chang CC, Chen CC, Kurokawa U, et al., 2011a. Accurate sensing of LED spectra via low-cost spectrum sensors. IEEE Sens J, 11(11):2869–2877. https://doi.org/10.1109/jsen.2011.2147302
Chang CC, Lin NT, Kurokawa U, et al., 2011b. Spectrum reconstruction for filter-array spectrum sensor from sparse template selection. Opt Eng, 50(11):114402. https://doi.org/10.1117/1.3645086
Chang CC, Chuang YC, Wu CT, et al., 2014. A low-cost mobile device for skin tone measurement using filter array spectrum sensor. Sensors, p.499–502. https://doi.org/10.1109/ICSENS.2014.6985044
Correia J, de Graaf G, Kong SH, et al., 2000. Single-chip CMOS optical microspectrometer. Sens Actuat A Phys, 82(1–3):191–197. https://doi.org/10.1016/s0924-4247(99)00369-6
Craig B, Shrestha VR, Meng JJ, et al., 2018. Experimental demonstration of infrared spectral reconstruction using plasmonic metasurfaces. Opt Lett, 43(18):4481–4484. https://doi.org/10.1364/ol.43.004481
Crozier KB, Sundaramurthy A, Kino GS, et al., 2003. Optical antennas: resonators for local field enhancement. J Appl Phys, 94(7):4632–4642. https://doi.org/10.1063/1.1602956
Cull EC, Gehm ME, Brady DJ, et al., 2007. Dispersion multiplexing with broadband filtering for miniature spectrometers. Appl Opt, 46(3):365–374. https://doi.org/10.1364/ao.46.000365
Das AJ, Wahi A, Kothari I, et al., 2016. Ultra-portable, wireless smartphone spectrometer for rapid, non-destructive testing of fruit ripeness. Sci Rep, 6:32504. https://doi.org/10.1038/srep32504
Decker JA, 1971. Experimental realization of the multiplex advantage with a Hadamard-transform spectrometer. Appl Opt, 10(3):510–514. https://doi.org/10.1364/AO.10.000510
Diaz N, Rueda H, Arguello H, 2018. Adaptive filter design via a gradient thresholding algorithm for compressive spectral imaging. Appl Opt, 57(17):4890–4900. https://doi.org/10.1364/AO.57.004890
Donoho DL, 2006. Compressed sensing. IEEE Trans Inform Theory, 52(4):1289–1306. https://doi.org/10.1109/tit.2006.871582
Duarte MF, Davenport MA, Takhar D, et al., 2008. Singlepixel imaging via compressive sampling. IEEE Signal Process Mag, 25(2):83–91. https://doi.org/10.1109/msp.2007.914730
Faraji-Dana M, Arbabi E, Arbabi A, et al., 2018. Compact folded metasurface spectrometer. Nat Commun, 9(1): 4196. https://doi.org/10.1038/s41467-018-06495-5
Feller SD, Chen H, Brady DJ, et al., 2007. Multiple order coded aperture spectrometer. Opt Expr, 15(9):5625–5630. https://doi.org/10.1364/OE.15.005625
Ford BK, Descour MR, Lynch RM, 2001. Large-image-format computed tomography imaging spectrometer for fluorescence microscopy. OptExpr, 9(9):444–453. https://doi.org/10.1364/oe.9.000444
Galvis L, Lau D, Ma X, et al., 2017. Coded aperture design in compressive spectral imaging based on side information. Appl Opt, 56(22):6332–6340. https://doi.org/10.1364/ao.56.006332
Gao L, Wang LV, 2016. A review of snapshot multidimensional optical imaging: measuring photon tags in parallel. Phys Rep, 616:1–37. https://doi.org/10.1016/j.physrep.2015.12.004
Gehm ME, McCain ST, Pitsianis NP, et al., 2006. Static two-dimensional aperture coding for multimodal, multiplex spectroscopy. Appl Opt, 45(13):2965–2974. https://doi.org/10.1364/ao.45.002965
Gehm ME, John R, Brady DJ, et al., 2007. Single-shot compressive spectral imaging with a dual-disperser architecture. Opt Expr, 15(21):14013–14027. https://doi.org/10.1364/oe.15.014013
Girard A, 1963. Spectromètre à grilles. Appl Opt, 2(1):79–87 (in French). https://doi.org/10.1364/ao.2.000079
Goel M, Whitmire E, Mariakakis A, et al., 2015. HyperCam: hyperspectral imaging for ubiquitous computing applications. Proc ACM Int Joint Conf on Pervasive and Ubiquitous Computing, p.145–156. https://doi.org/10.1145/2750858.2804282
Golay MJE, 1949. Multi-slit spectrometry. J Opt Soc Am, 39(6):437–444. https://doi.org/10.1364/josa.39.000437
Golay MJE, 1951. Static multislit spectrometry and its application to the panoramic display of infrared spectra. J Opt Soc Am, 41(7):468–472. https://doi.org/10.1364/josa.41.000468
Hagen NA, Kudenov MW, 2013. Review of snapshot spectral imaging technologies. Opt Eng, 52(9):090901. https://doi.org/10.1117/1.oe.52.9.090901
Hansen P, Strong J, 1972. High resolution Hadamard transform spectrometer. Appl Opt, 11(3):502–506. https://doi.org/10.1364/AO.11.000502
Hayes MH, 1996. Statistical Digital Signal Processing and Modeling. John Wiley & Sons, New York, USA.
Hinojosa CA, Correa CV, Arguello H, et al., 2016. Compressive spectral imaging using multiple snapshot colored-mosaic detector measurements. Computational Imaging, Article 987004. https://doi.org/10.1117/12.2224369
Huang E, Ma Q, Liu ZW, 2017. Etalon array reconstructive spectrometry. Sci Rep, 7:40693. https://doi.org/10.1038/srep40693
Jacquinot P, 1960. New developments in interference spectroscopy. Rep Prog Phys, 23(1):267–312. https://doi.org/10.1088/0034-4885/23/1/305
Kats MA, Blanchard R, Genevet P, et al., 2013. Thermal tuning of mid-infrared plasmonic antenna arrays using a phase change material. Opt Lett, 38(3):368–370. https://doi.org/10.1364/ol.38.000368
Kirchhoff GR, Bunsen RW, 1861. Chemische analyse durch spectralbeobachtungen. Ann Phys Chem, 189:3370381 (in German). https://doi.org/10.1002/andp.18611890702
Kita DM, Miranda B, Favela D, et al., 2018. High-performance and scalable on-chip digital Fourier transform spectroscopy. Nat Commun, 9(1):4405. https://doi.org/10.1038/s41467-018-06773-2
Kudenov MW, Dereniak EL, 2012. Compact real-time birefringent imaging spectrometer. Opt Expr, 20(16):17973–17986. https://doi.org/10.1364/oe.20.017973
Kuiteing SK, Coluccia G, Barducci A, et al., 2014. Compressive hyperspectral imaging using progressive total variation. IEEE Int Conf on Acoustics, Speech and Signal Processing, p.7794–7798. https://doi.org/10.1109/ICASSP.2014.6855117
Kurokawa U, Choi BI, Chang CC, 2011. Filter-based miniature spectrometers: spectrum reconstruction using adaptive regularization. IEEE Sens J, 11(7):1556–1563. https://doi.org/10.1109/jsen.2010.2103054
Li ZY, Palacios E, Butun S, et al., 2015. Visible-frequency metasurfaces for broadband anomalous reflection and high-efficiency spectrum splitting. Nano Lett, 15(3): 1615–1621. https://doi.org/10.1021/nl5041572
Momeni B, Hosseini ES, Askari M, et al., 2009. Integrated photonic crystal spectrometers for sensing applications. Opt Commun, 282(15):3168–3171. https://doi.org/10.10167/j.optcom.2009.04.052
Newton I, 1979. Opticks (2nd Ed.). Dover Publications Inc., New York, USA.
Okamoto T, Yamaguchi I, 1991. Simultaneous acquisition of spectral image information. Opt Lett, 16(16):1277–1279. https://doi.org/10.1364/ol.16.001277
Oliver J, Lee W, Park S, et al., 2012. Improving resolution of miniature spectrometers by exploiting sparse nature of signals. Opt Expr, 20(3):2613–2625. https://doi.org/10.1364/oe.20.002613
Oliver J, Lee WB, Lee HN, 2013. Filters with random transmittance for improving resolution in filter-array-based spectrometers. Opt Expr, 21(4):3969–3989. https://doi.org/10.1364/oe.21.003969
Pervez NK, Cheng W, Jia Z, et al., 2010. Photonic crystal spectrometer. Opt Expr, 18(8):8277–8285. https://doi.org/10.1364/oe.18.008277
Phillips PG, Briotta DA, 1974. Hadamard-transform spectrometry of the atmospheres of Earth and Jupiter. Appl Opt, 13(10):2233–2235. https://doi.org/10.1364/AO.13.002233
Rajwade A, Kittle D, Tsai TH, et al., 2013. Coded hyperspectral imaging and blind compressive sensing. SIAM J Imag Sci, 6(2):782–812. https://doi.org/10.1137/120875302
Redding B, Liew SF, Sarma R, et al., 2013. Compact spectrometer based on a disordered photonic chip. Nat Photon, 7(9):746–751. https://doi.org/10.1038/nphoton.2013.190
Ren WY, Fu C, Arce GR, 2018. The first result of compressed channeled imaging spectropolarimeter. Imaging and Applied Optics, Article JTu4A.21. https://doi.org/10.1364/3D.2018.JTu4A.21
Rueda H, Arguello H, Arce GR, 2015. DMD-based implementation of patterned optical filter arrays for compressive spectral imaging. J Opt Soc Am A, 32(1):80–89. https://doi.org/10.1364/JOSAA.32.000080
Shaltout A, Liu JJ, Kildishev A, et al., 2015. Photonic spin Hall effect in gap—plasmon metasurfaces for on-chip chiroptical spectroscopy. Optica, 2(10):860–863. https://doi.org/10.1364/optica.2.000860
Soldevila F, Irles E, Durán V, et al., 2013. Single-pixel polarimetric imaging spectrometer by compressive sensing. Appl Phys B, 113(4):551–558. https://doi.org/10.1007/s00340-013-5506-2
Sun T, Kelly K, 2009. Compressive sensing hyperspectral imager. Computational Optical Sensing and Imaging, Article CTuA5. https://doi.org/10.1364/COSI.2009.CTuA5
Swift RD, Wattson RB, Decker JA, et al., 1976. Hadamard transform imager and imaging spectrometer. Appl Opt, 15(6):1595–1609. https://doi.org/10.1364/AO.15.001595
Takhar D, Laska JN, Wakin MB, et al., 2006. A new compressive imaging camera architecture using optical-domain compression. Computational Imaging IV, Article 606509. https://doi.org/10.1117/12.659602
Vigneau E, Devaux MF, Qannari EM, et al., 1997. Principal component regression, ridge regression and ridge principal component regression in spectroscopy calibration. J Chemomet, 11(3):239–249. https://doi.org/10.1002/(SICI)1099-128X(199705)11:3<239::AID-CEM470>3.0.co;2-A
Wagadarikar A, John R, Willett R, et al., 2008. Single disperser design for coded aperture snapshot spectral imaging. Appl Opt, 47(10):B44–B51. https://doi.org/10.1364/ao.47.000b44
Wagadarikar AA, Pitsianis NP, Sun XB, et al., 2009. Video rate spectral imaging using a coded aperture snapshot spectral imager. Opt Expr, 17(8):6368–6388. https://doi.org/10.1364/oe.17.006368
Wang LZ, Xiong ZW, Gao DH, et al., 2015. Dual-camera design for coded aperture snapshot spectral imaging. Appl Opt, 54(4):848–858. https://doi.org/10.1364/ao.54.000848
Wang LZ, Xiong ZW, Shi GM, et al., 2017. Adaptive nonlocal sparse representation for dual-camera compressive hyperspectral imaging. IEEE Trans Patt Anal Mach Intell, 39(10):2104–2111. https://doi.org/10.1109/tpami.2016.2621050
Wang Z, Yi S, Chen A, et al., 2019. Single-shot on-chip spectral sensors based on photonic crystal slabs. Nat Commun, 10(1):1020. https://doi.org/10.1038/s41467-019-08994-5
Willett RM, Gehm ME, Brady DJ, 2007. Multiscale reconstruction for computational spectral imaging. Computational Imaging V, Article 64980L. https://doi.org/10.1117/12.715711
Wolffenbuttel RF, 2004. State-of-the-art in integrated optical microspectrometers. IEEE Trans Instrum Meas, 53(1): 197–202. https://doi.org/10.1109/tim.2003.821490
Yetzbacher MK, Miller CW, Boudreau AJ, et al., 2014. Multiple-order staircase etalon spectroscopy. Next-Generation Spectroscopic Technologies VII, Article 910104. https://doi.org/10.1117/12.2049848
Author information
Authors and Affiliations
Corresponding author
Additional information
Project supported by the National Key R&D Program of China (No. 2018YFA0701400), the Fundamental Research Funds for the Central Universities, China (No. 2019QNA5006), and the ZJU-Sunny Photonics Innovation Center, China (No. 2019-01)
Contributors
Haifeng LI and Xu LIU guided the investigation. Hongya SONG, Wenyi ZHANG, and Xiang HAO investigated the main information. Hongya SONG summarized the information and drafted the manuscript. Wenyi ZHANG and Xiang HAO helped organize the manuscript. Hongya SONG and Xiang HAO revised and finalized the paper.
Compliance with ethics guidelines
Hongya SONG, Wenyi ZHANG, Hai-feng LI, Xu LIU, and Xiang HAO declare that they have no conflict of interest.
Hongya SONG, first author of this invited paper, received his BS in electronics engineering in 2016 from Wuhan University. He is currently a PhD candidate in optical engineering at Zhejiang University. His research interests include color science, spectral imaging, and computational imaging.
Xiang HAO, corresponding author of this invited paper, is a PI of optical science and technology at Zhejiang University. He received his PhD in optical engineering in 2014 from Zhejiang University. After spending more than four years at Yale University School of Medicine as an associate research scientist, Dr. HAO returned to Zhejiang University in late 2018. He also had short visits at other leading institutes, including Janelia Research Campus of Howard Hughes Medical Institute and University of Oxford. As an optical physicist and biophysicist by training, Dr. HAO has been a long-time contributor to the development of super resolution light microscopy, spectroscopy, photolithography, and applications of these techniques to address biological questions. He is now a corresponding expert of Front Inform Technol Electron Eng. He has over 50 peer-reviewed publications and has been granted over 30 patents.
Rights and permissions
About this article
Cite this article
Song, H., Zhang, W., Li, H. et al. Review of compact computational spectral information acquisition systems. Front Inform Technol Electron Eng 21, 1119–1133 (2020). https://doi.org/10.1631/FITEE.1900266
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1631/FITEE.1900266