Acta Optica Sinica, Volume. 43, Issue 15, 1511001(2023)

Advances in Speckle and Compressive Computational Imaging

Xia Wang*, Xu Ma**, Jun Ke***, Si He, Xiaowen Hao, Jingwen Lei, and Kai Ma
Author Affiliations
  • Key Laboratory of Optoelectronic Imaging Technology and Systems, Ministry of Education, School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China
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    References(73)

    [1] Bertolotti J, van Putten E G, Blum C et al. Non-invasive imaging through opaque scattering layers[J]. Nature, 491, 232-234(2012).

    [2] Katz O, Heidmann P, Fink M et al. Non-invasive single-shot imaging through scattering layers and around corners via speckle correlations[J]. Nature Photonics, 8, 784-790(2014).

    [3] Wu T F, Katz O, Shao X P et al. Single-shot diffraction-limited imaging through scattering layers via bispectrum analysis[J]. Optics Letters, 41, 5003-5006(2016).

    [4] Yuan Y, Chen H. Dynamic noninvasive imaging through turbid media under low signal-noise-ratio[J]. New Journal of Physics, 22, 093046(2020).

    [5] Li X H, Stevens A, Greenberg J A et al. Single-shot memory-effect video[J]. Scientific Reports, 8, 13402(2018).

    [6] Wang Y B, Cao J, Xu C Q et al. Moving target tracking and imaging through scattering media via speckle-difference-combined bispectrum analysis[J]. IEEE Photonics Journal, 11, 6101514(2019).

    [7] Lu D J, Liao M H, He W Q et al. Tracking moving object beyond the optical memory effect[J]. Optics and Lasers in Engineering, 124, 105815(2020).

    [8] Wang X Y, Jin X, Li J Q. Blind position detection for large field-of-view scattering imaging[J]. Photonics Research, 8, 920-928(2020).

    [9] Shi Y Y, Liu Y W, Wang J M et al. Non-invasive depth-resolved imaging through scattering layers via speckle correlations and parallax[J]. Applied Physics Letters, 110, 231101(2017).

    [10] Li W, Liu J T, He S F et al. Multitarget imaging through scattering media beyond the 3D optical memory effect[J]. Optics Letters, 45, 2692-2695(2020).

    [11] Guo E L, Zhu S, Sun Y et al. Learning-based method to reconstruct complex targets through scattering medium beyond the memory effect[J]. Optics Express, 28, 2433-2446(2020).

    [12] Zhu S, Guo E L, Gu J et al. Imaging through unknown scattering media based on physics-informed learning[J]. Photonics Research, 9, B210-B219(2021).

    [13] Li X H, Greenberg J A, Gehm M E. Single-shot multispectral imaging through a thin scatterer[J]. Optica, 6, 864-871(2019).

    [14] Sahoo S K, Tang D L, Dang C. Single-shot multispectral imaging with a monochromatic camera[J]. Optica, 4, 1209-1213(2017).

    [15] Shi Y J, Guo E L, Bai L F et al. Non-invasive imaging through scattering medium beyond the memory effect via polarization-modulation[J]. Optics Communications, 511, 127857(2022).

    [16] Duarte M F, Davenport M A, Takhar D et al. Single-pixel imaging via compressive sampling[J]. IEEE Signal Processing Magazine, 25, 83-91(2008).

    [17] Iliadis M, Spinoulas L, Katsaggelos A K. Deep fully-connected networks for video compressive sensing[J]. Digital Signal Processing, 72, 9-18(2018).

    [18] Ke J, Lam E Y. Object reconstruction in block-based compressive imaging[J]. Optics Express, 20, 22102-22117(2012).

    [19] Li L, Fang Y, Liu L et al. Overview of compressed sensing: sensing model, reconstruction algorithm, and its applications[J]. Applied Sciences, 10, 5909(2020).

    [20] Llull P, Liao X J, Yuan X et al. Coded aperture compressive temporal imaging[J]. Optics Express, 21, 10526-10545(2013).

    [21] Li J N, Zhang S L, Huang T J. Multi-scale 3D convolution network for video based person re-identification[J]. Proceedings of the AAAI Conference on Artificial Intelligence, 8618-8625(2019).

    [23] Kulkarni K, Lohit S, Turaga P et al. ReconNet: non-iterative reconstruction of images from compressively sensed measurements[C], 449-458(2016).

    [24] Ke J, Sui D, Wei P. Fast object reconstruction in block-based compressive low-light-level imaging[J]. Proceedings of SPIE, 9301, 930136(2014).

    [25] Wang J Y, Ke J. High-resolution three-dimensional imaging with compress sensing[J]. Proceedings of SPIE, 10020, 1002014(2016).

    [26] Sun Y T, Yuan X, Pang S. Compressive high-speed stereo imaging[J]. Optics Express, 25, 18182-18190(2017).

    [27] Xu H, Wang X J. Applications of multispectral/hyperspectral imaging technologies in military[J]. Infrared and Laser Engineering, 36, 13-17(2007).

    [28] Gao Z D, Gao H X, Zhu Y Y et al. Review of snapshot spectral imaging technologies[J]. Optics and Precision Engineering, 28, 1323-1343(2020).

    [29] Wang Y W, Reder N P, Kang S et al. Multiplexed optical imaging of tumor-directed nanoparticles: a review of imaging systems and approaches[J]. Nanotheranostics, 1, 369-388(2017).

    [30] Wagadarikar A, John R, Willett R et al. Single disperser design for coded aperture snapshot spectral imaging[J]. Applied Optics, 47, B44(2008).

    [31] Gehm M E, John R, Brady D J et al. Single-shot compressive spectral imaging with a dual-disperser architecture[J]. Optics Express, 15, 14013-14027(2007).

    [32] Ma C G, Cao X, Tong X et al. Acquisition of high spatial and spectral resolution video with a hybrid camera system[J]. International Journal of Computer Vision, 110, 141-155(2014).

    [33] Arguello H, Arce G R. Code aperture optimization for spectrally agile compressive imaging[J]. Journal of the Optical Society of America A, 28, 2400-2413(2011).

    [34] Arguello H, Arce G R. Colored coded aperture design by concentration of measure in compressive spectral imaging[J]. IEEE Transactions on Image Processing, 23, 1896-1908(2014).

    [35] Correa C V, Arguello H, Arce G R. Spatiotemporal blue noise coded aperture design for multi-shot compressive spectral imaging[J]. Journal of the Optical Society of America A, 33, 2312-2322(2016).

    [36] Lin X, Wetzstein G, Liu Y B et al. Dual-coded compressive hyperspectral imaging[J]. Optics Letters, 39, 2044-2047(2014).

    [37] Shao X P, Zhong C, Du J et al. Super-resolution imaging method using multi-value compressed coded aperture[J]. Journal of Optoelectronics·Laser, 23, 1189-1195(2012).

    [38] Ma C G, Cao X, Wu R H et al. Content-adaptive high-resolution hyperspectral video acquisition with a hybrid camera system[J]. Optics Letters, 39, 937-940(2014).

    [39] Xiong Z W, Shi Z, Li H Q et al. HSCNN: CNN-based hyperspectral image recovery from spectrally undersampled projections[C], 518-525(2018).

    [40] Miao X, Yuan X, Pu Y C et al. Lambda-net: reconstruct hyperspectral images from a snapshot measurement[C], 4058-4068(2020).

    [42] Zheng S M, Liu Y, Meng Z Y et al. Deep plug-and-play priors for spectral snapshot compressive imaging[J]. Photonics Research, 9, B18-B29(2021).

    [43] Cai Y H, Lin J, Hu X W et al. Mask-guided spectral-wise transformer for efficient hyperspectral image reconstruction[C], 17481-17490(2022).

    [44] Ma K, Wang X, He S et al. Learning to image and track moving objects through scattering media via speckle difference[J]. Optics & Laser Technology, 159, 108925(2023).

    [45] He S, Wang X A, Ma K et al. Recursion-driven bispectral imaging for dynamic scattering scenes[J]. Optics Letters, 48, 287-290(2023).

    [46] Ma K, Wang X A, He S et al. Plug-and-play algorithm for imaging through scattering media under ambient light interference[J]. Optics Letters, 48, 1754-1757(2023).

    [47] Gan L. Block compressed sensing of natural images[C], 403-406(2007).

    [48] Mahalanobis A, Shilling R, Murphy R et al. Recent results of medium wave infrared compressive sensing[J]. Applied Optics, 53, 8060-8070(2014).

    [49] Wu Z M, Wang X A. Focal plane array-based compressive imaging in medium wave infrared: modeling, implementation, and challenges[J]. Applied Optics, 58, 8433-8441(2019).

    [50] Chen H J, Asif M S, Sankaranarayanan A C et al. FPA-CS: focal plane array-based compressive imaging in short-wave infrared[C], 2358-2366(2015).

    [51] Wu Z M, Wang X. DMD mask construction to suppress blocky structural artifacts for medium wave infrared focal plane array-based compressive imaging[J]. Sensors, 20, 900(2020).

    [52] Wu Z M, Wang X. Non-uniformity correction for medium wave infrared focal plane array-based compressive imaging[J]. Optics Express, 28, 8541-8559(2020).

    [53] Wu Z M, Wang X. Stray light correction for medium wave infrared focal plane array-based compressive imaging[J]. Optics Express, 28, 19097-19112(2020).

    [54] Ke J, Zhang L X, Lam E Y. Temporal compressed measurements for block-wise compressive imaging[C], JW4B.1(2019).

    [55] Zhang L X, Ke J, Chi S et al. High-resolution fast mid-wave infrared compressive imaging[J]. Optics Letters, 46, 2469-2472(2021).

    [56] Cui C, Xu L H, Yang B Y et al. Meta-TR: meta-attention spatial compressive imaging network with swin transformer[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 15, 6236-6247(2022).

    [57] Cui C, Ke J. Spatial compressive imaging deep learning framework using joint input of multi-frame measurements and degraded maps[J]. Optics Express, 30, 1235-1248(2022).

    [58] Yuan X, Brady D J, Katsaggelos A K. Snapshot compressive imaging: theory, algorithms, and applications[J]. IEEE Signal Processing Magazine, 38, 65-88(2021).

    [59] Zhang L X, Ke J, Zhou Q. Temporal compressive imaging for video[J]. Proceedings of SPIE, 10620, 1062014(2018).

    [60] Zhang L X, Ke J, Lam E Y. A deep learning approach for reconstruction in temporal compressed imaging[C], CW4B.3(2020).

    [61] Zhang L X, Lam E Y, Ke J. Temporal compressive imaging reconstruction based on a 3D-CNN network[J]. Optics Express, 30, 3577-3591(2022).

    [62] Zhou Q, Ke J, Lam E Y. Near-infrared temporal compressive imaging for video[J]. Optics Letters, 44, 1702-1705(2019).

    [63] Zhou Q, Ke J, Lam E Y. Dual-waveband temporal compressive imaging[C], CTu2A.8(2019).

    [64] Ke J, Zhang L X, Zhou Q et al. Broad dual-band temporal compressive imaging with optical calibration[J]. Optics Express, 29, 5710-5729(2021).

    [65] Zhao D, Lam E Y, Ke J. Spatial-temporal compressive imaging using an unfolding network[C], CW1B.5(2022).

    [66] Zhao D, Ke J. Two-step spatial-temporal compressive sensing imaging[J]. Proceedings of SPIE, 11896, 118961B(2021).

    [67] Zhao X H, Ma X. Off-axis aberration correction for a reflective coded aperture snapshot spectral imager[J]. Optics Letters, 47, 1202-1205(2022).

    [68] Wang P, Ma X, Zhao Q L. Comparison of reconstruction algorithm based on different priors for snapshot compressive spectral imaging[J]. Proceedings of SPIE, 12634(2023).

    [69] Zhang H, Ma X, Zhao X H et al. Compressive hyperspectral image classification using a 3D coded convolutional neural network[J]. Optics Express, 29, 32875-32891(2021).

    [70] Zhang H, Ma X, Lau D L et al. Compressive spectral imaging based on hexagonal blue noise coded apertures[J]. IEEE Transactions on Computational Imaging, 6, 749-763(2020).

    [71] Zhang H, Ma X, Arce G R. Compressive spectral imaging approach using adaptive coded apertures[J]. Applied Optics, 59, 1924-1938(2020).

    [72] Figueiredo M A T, Nowak R D, Wright S J. Gradient projection for sparse reconstruction: application to compressed sensing and other inverse problems[J]. IEEE Journal of Selected Topics in Signal Processing, 1, 586-597(2007).

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    Xia Wang, Xu Ma, Jun Ke, Si He, Xiaowen Hao, Jingwen Lei, Kai Ma. Advances in Speckle and Compressive Computational Imaging[J]. Acta Optica Sinica, 2023, 43(15): 1511001

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    Paper Information

    Category: Imaging Systems

    Received: Mar. 29, 2023

    Accepted: May. 15, 2023

    Published Online: Jul. 28, 2023

    The Author Email: Wang Xia (angelniuniu@bit.edu.cn), Ma Xu (maxu@bit.edu.cn), Ke Jun (jke@bit.edu.cn)

    DOI:10.3788/AOS230735

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