Acta Optica Sinica, Volume. 44, Issue 7, 0711001(2024)
High-Quality Image Reconstruction Characteristic Function for Single-Pixel Compressive Imaging
[1] Cheng J, Han S S. Incoherent coincidence imaging and its applicability in X-ray diffraction[J]. Physical Review Letters, 92, 093903(2004).
[2] Bennink R S, Bentley S J, Boyd R W et al. Quantum and classical coincidence imaging[J]. Physical Review Letters, 92, 033601(2004).
[3] Shapiro J H, Boyd R W. The physics of ghost imaging[J]. Quantum Information Processing, 11, 949-993(2012).
[4] Graham-Rowe D. Pixel power[J]. Nature Photonics, 1, 211-212(2007).
[5] 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).
[6] Gibson G M, Johnson S D, Padgett M J. Single-pixel imaging 12 years on: a review[J]. Optics Express, 28, 28190-28208(2020).
[7] Edgar M P, Gibson G M, Padgett M J. Principles and prospects for single-pixel imaging[J]. Nature Photonics, 13, 13-20(2019).
[8] Zhao C Q, Gong W L, Chen M L et al. Ghost imaging lidar via sparsity constraints[J]. Applied Physics Letters, 101, 141123(2012).
[9] Erkmen B I. Computational ghost imaging for remote sensing[J]. Journal of the Optical Society of America A, 29, 782-789(2012).
[10] Sun B, Edgar M P, Bowman R et al. 3D computational imaging with single-pixel detectors[J]. Science, 340, 844-847(2013).
[11] Gong W L, Zhao C Q, Yu H et al. Three-dimensional ghost imaging lidar via sparsity constraint[J]. Scientific Reports, 6, 26133(2016).
[12] Yu H, Lu R H, Han S S et al. Fourier-transform ghost imaging with hard X rays[J]. Physical Review Letters, 117, 113901(2016).
[13] Pelliccia D, Rack A, Scheel M et al. Experimental X-ray ghost imaging[J]. Physical Review Letters, 117, 113902(2016).
[14] Clemente P, Durán V, Torres-Company V et al. Optical encryption based on computational ghost imaging[J]. Optics Letters, 35, 2391-2393(2010).
[15] Gong W L, Han S S. A method to improve the visibility of ghost images obtained by thermal light[J]. Physics Letters A, 374, 1005-1008(2010).
[16] Ferri F, Magatti D, Lugiato L A et al. Differential ghost imaging[J]. Physical Review Letters, 104, 253603(2010).
[17] Gong W L. High-resolution pseudo-inverse ghost imaging[J]. Photonics Research, 3, 234-237(2015).
[18] Sun B Q, Welsh S S, Edgar M P et al. Normalized ghost imaging[J]. Optics Express, 20, 16892-16901(2012).
[19] Katz O, Bromberg Y, Silberberg Y. Compressive ghost imaging[J]. Applied Physics Letters, 95, 131110(2009).
[20] Du J, Gong W L, Han S S. The influence of sparsity property of images on ghost imaging with thermal light[J]. Optics Letters, 37, 1067-1069(2012).
[21] Lyu M, Wang W, Wang H et al. Deep-learning-based ghost imaging[J]. Scientific Reports, 7, 17865(2017).
[22] Vaz P G, Amaral D, Ferreira L F R et al. Image quality of compressive single-pixel imaging using different Hadamard orderings[J]. Optics Express, 28, 11666-11681(2020).
[23] 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, 18, 065703(2016).
[24] Yu W K. Super sub-Nyquist single-pixel imaging by means of cake-cutting Hadamard basis sort[J]. Sensors, 19, 4122(2019).
[25] 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, 7, 3464(2017).
[26] Zhou C, Tian T, Gao C et al. Multi-resolution progressive computational ghost imaging[J]. Journal of Optics, 21, 055702(2019).
[27] 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, 13, 071101(2015).
[28] Hu C Y, Tong Z S, Liu Z T et al. Optimization of light fields in ghost imaging using dictionary learning[J]. Optics Express, 27, 28734-28749(2019).
[29] Higham C F, Murray-Smith R, Padgett M J et al. Deep learning for real-time single-pixel video[J]. Scientific Reports, 8, 2369(2018).
[30] Zhao Z D, Yang Z H, Yu Y J. Research progress of single pixel imaging[J]. Chinese Journal of Lasers, 49, 1917001(2022).
[31] Sun M J, Yan S M, Wang S Y. Reconstruction algorithms for ghost imaging and single-pixel imaging[J]. Laser & Optoelectronics Progress, 59, 0200001(2022).
[32] Zhao H, Wang X Q, Gao C et al. Second-order cumulants ghost imaging[J]. Chinese Optics Letters, 20, 112602(2022).
[33] Sun Y S, Huang J, Shi D F et al. Cosinusoidal encoding multiplexed multispectral ghost imaging[J]. Chinese Journal of Lasers, 50, 1317001(2023).
[34] Candes E J, Wakin M B. An introduction to compressive sampling[J]. IEEE Signal Processing Magazine, 25, 21-30(2008).
[35] 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).
[36] Donoho D L, Elad M, Temlyakov V N. Stable recovery of sparse overcomplete representations in the presence of noise[J]. IEEE Transactions on Information Theory, 52, 6-18(2006).
[37] Elad M. Optimized projections for compressed sensing[J]. IEEE Transactions on Signal Processing, 55, 5695-5702(2007).
[38] Yi R J, Cui C, Wu B et al. A new method of measurement matrix optimization for compressed sensing based on alternating minimization[J]. Mathematics, 9, 329(2021).
[39] Li Z J, Zhao Q, Gong W L. Distorted point spread function and image reconstruction for ghost imaging[J]. Optics and Lasers in Engineering, 139, 106486(2021).
Get Citation
Copy Citation Text
Shichang Ju, Junjie Cai, Wenlin Gong. High-Quality Image Reconstruction Characteristic Function for Single-Pixel Compressive Imaging[J]. Acta Optica Sinica, 2024, 44(7): 0711001
Category: Imaging Systems
Received: Nov. 6, 2023
Accepted: Jan. 11, 2024
Published Online: Apr. 11, 2024
The Author Email: Gong Wenlin (wlgong@suda.edu.cn)
CSTR:32393.14.AOS231741