Robust Entangled-Photon Ghost Imaging with Compressive Sensing

This work experimentally demonstrates that the imaging quality of quantum ghost imaging (GI) with entangled photons can be significantly improved by properly handling the errors caused by the imperfection of optical devices. We also consider compressive GI to reduce the number of measurements and thereby the data acquisition time. The image reconstruction is formulated as a sparse total least square problem which is solved with an iterative algorithm. Our experiments show that, compared with existing methods, the new method can achieve a significant performance gain in terms of mean square error and peak signal–noise ratio.

[1]  Zibang Zhang,et al.  Fast Fourier single-pixel imaging via binary illumination , 2017, Scientific Reports.

[2]  Shih,et al.  Optical imaging by means of two-photon quantum entanglement. , 1995, Physical review. A, Atomic, molecular, and optical physics.

[3]  G. Teschke,et al.  Compressive sensing principles and iterative sparse recovery for inverse and ill-posed problems , 2010 .

[4]  G. Brida,et al.  Systematic analysis of signal-to-noise ratio in bipartite ghost imaging with classical and quantum light , 2011, 1103.1281.

[5]  Shih,et al.  Two-photon geometric optics. , 1996, Physical review. A, Atomic, molecular, and optical physics.

[6]  Wenlin Gong,et al.  Super-resolution ghost imaging via compressive sampling reconstruction , 2009, 0910.4823.

[7]  Marco Genovese,et al.  Real applications of quantum imaging , 2016, 1601.06066.

[8]  Mert Pilanci,et al.  Recovery of sparse perturbations in Least Squares problems , 2011, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[9]  Shensheng Han,et al.  Quantum limits of super-resolution of optical sparse objects via sparsity constraint. , 2012, Optics express.

[10]  Robert W. Boyd,et al.  Entangled-photon compressive ghost imaging , 2011 .

[11]  Shih,et al.  Observation of two-photon "ghost" interference and diffraction. , 1995, Physical review letters.

[12]  Jong Chul Ye,et al.  Compressed sensing metal artifact removal in dental CT , 2009, 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[13]  Jean-Luc Starck,et al.  Compressed Sensing in Astronomy , 2008, IEEE Journal of Selected Topics in Signal Processing.

[14]  Shiqing Zhang,et al.  Robust Facial Expression Recognition via Compressive Sensing , 2012, Sensors.

[15]  Emmanuel J. Candès,et al.  Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information , 2004, IEEE Transactions on Information Theory.

[16]  Robert W. Boyd,et al.  Compressive Object Tracking using Entangled Photons , 2013 .

[17]  Yi Zhou,et al.  Simultaneous Radio Frequency and Wideband Interference Suppression in SAR Signals via Sparsity Exploitation in Time–Frequency Domain , 2018, IEEE Transactions on Geoscience and Remote Sensing.

[18]  E. Candès,et al.  Stable signal recovery from incomplete and inaccurate measurements , 2005, math/0503066.

[19]  Ling-An Wu,et al.  Adaptive compressive ghost imaging based on wavelet trees and sparse representation. , 2014, Optics express.

[20]  D. Klyshko Photons Nonlinear Optics , 1988 .

[21]  O. Katz,et al.  Compressive ghost imaging , 2009, 0905.0321.

[22]  Wenlin Gong,et al.  Performance analysis of ghost imaging lidar in background light environment , 2017 .

[23]  R. Boyd,et al.  "Two-Photon" coincidence imaging with a classical source. , 2002, Physical review letters.

[24]  Robert W Boyd,et al.  Resolution limits of quantum ghost imaging. , 2018, Optics express.

[25]  Jesús Lancis,et al.  Optical encryption based on computational ghost imaging. , 2010, Optics letters.

[26]  Roderick Murray-Smith,et al.  Deep learning for real-time single-pixel video , 2018, Scientific Reports.

[27]  Y. Shih Quantum Imaging , 2007, IEEE Journal of Selected Topics in Quantum Electronics.

[28]  Joel A. Tropp,et al.  Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit , 2007, IEEE Transactions on Information Theory.

[29]  Robert W Boyd,et al.  Quantum and classical coincidence imaging. , 2004, Physical review letters.

[30]  Emmanuel J. Candès,et al.  Near-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies? , 2004, IEEE Transactions on Information Theory.

[31]  S. Frick,et al.  Compressed Sensing , 2014, Computer Vision, A Reference Guide.

[32]  Robert W. Boyd,et al.  Imaging with a small number of photons , 2014, Nature Communications.

[33]  M. Teich,et al.  Duality between partial coherence and partial entanglement , 2000 .

[34]  Jeffrey H. Shapiro,et al.  The physics of ghost imaging , 2012, Quantum Information Processing.

[35]  Rafał Kotyński,et al.  Real-time single-pixel video imaging with Fourier domain regularization. , 2018, Optics express.