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Robust Entangled-Photon Ghost Imaging with Compressive Sensing

Journal Article


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Abstract


  • 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.

Publication Date


  • 2019

Citation


  • J. Li, W. Gao, J. Qian, Q. Guo, J. Xi & C. H. Ritz, "Robust Entangled-Photon Ghost Imaging with Compressive Sensing," Sensors, vol. 19, (1) pp. 192-1-192-11, 2019.

Scopus Eid


  • 2-s2.0-85059798541

Ro Full-text Url


  • https://ro.uow.edu.au/cgi/viewcontent.cgi?article=3248&context=eispapers1

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers1/2241

Start Page


  • 192-1

End Page


  • 192-11

Volume


  • 19

Issue


  • 1

Place Of Publication


  • Switzerland

Abstract


  • 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.

Publication Date


  • 2019

Citation


  • J. Li, W. Gao, J. Qian, Q. Guo, J. Xi & C. H. Ritz, "Robust Entangled-Photon Ghost Imaging with Compressive Sensing," Sensors, vol. 19, (1) pp. 192-1-192-11, 2019.

Scopus Eid


  • 2-s2.0-85059798541

Ro Full-text Url


  • https://ro.uow.edu.au/cgi/viewcontent.cgi?article=3248&context=eispapers1

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers1/2241

Start Page


  • 192-1

End Page


  • 192-11

Volume


  • 19

Issue


  • 1

Place Of Publication


  • Switzerland