Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

Frontiers in Optics

Real Time Quantum Imaging via Compressed Sensing

Raphael C. Pooser, Benjamin J. Lawrie, Duncan Earl, Travis S. Humble, J. Schaake

Published Jan 1, 2012• 0 citations
Publisher

Abstract

We demonstrate quantum imaging in real time by measuring quantum noise reduction frame by frame in a moving quantum image. We obtain and reconstruct quantum images using a compressed measurement technique, demonstrating quantum compressive imaging.
DOI
10.1364/fio.2012.fm4c.3

Related papers

Real Time Quantum Imaging via Compressed Sensing

Raphael C. Pooser, Benjamin J. Lawrie, Duncan Earl +2 more

We demonstrate quantum imaging in real time by measuring quantum noise reduction frame by frame in a moving quantum image. We obtain and reconstruct quantum images using a compressed measurement technique, demonstrating quantum compressive imaging.

Conference on Lasers and Electro-Optics•Jan 1, 2012•0 citations

Quantum limits in compressed sensing of optical images

Hui Wang, Shensheng Han, Mikhail I. Kolobov

We discuss the ultimate quantum limits in compressed sensing, a new technique which allows for accurate reconstruction of so-called “sparse” signals even when the sampling rate is far below the Nyquist limit.

Conference on Lasers and Electro-Optics•Jan 1, 2012•1 citation

Three-dimensional quantum imaging of dynamic targets using quantum compressed sensing

Yang Liu, Jianyong Hu, Hongqi Niu +9 more

Quantum imaging based on entangled light sources exhibits enhanced background resistance compared to conventional imaging techniques in low-light conditions. However, direct imaging of dynamic targets remains challenging due to the limited count rate of entangled photons. In this paper, we propose a quantum imaging method based on quantum compressed sensing that leverages the strong correlation characteristics of entangled photons and the randomness inherent in photon pair generation and detection. This approach enables the construction of a compressed sensing system capable of directly imaging high-speed dynamic targets. The results demonstrate that our system successfully achieves imaging of a target rotating at a frequency of 10 kHz, while maintaining an impressive data compression rate of 10 −6 . This proposed method introduces a pioneering approach for the practical implementation of quantum imaging in real-world scenarios.

Optics Express•Jan 29, 2024•10 citations

Entropy, information and compressive sensing in the quantum domain

John Anthony Howell

I will discuss our recent efforts with single and double-pixel compressive sensing for applications in ghost imaging, low flux LIDAR, real-time object tracking, precision measurement and entanglement characterization.

Frontiers in Optics•Jan 1, 2012•0 citations

Compressive Quantum Ghost Imaging

Petros Zerom, Kam Wai Clifford Chan, John C. Howell +1 more

We experimentally demonstrate high-resolution quantum ghost imaging at the single photon level using single-pixel (bucket) detectors and compressive sensing algorithms. Compared to quantum ghost imaging experiments employing a raster scan, we show both shortened data acquisition time and a more economical use of photons for low-light-level-imaging.

International Conference on Quantum Information•Jan 1, 2011•1 citation

Compressive Quantum Sensing

John C. Howell

Compressive sensing utilizes sparsity to realize efficient image reconstruction. It is a valuable processing technique when cost, power, technology or computational overhead are limited or high. In the quantum domain technology usually limits efficient acquisition of weak or fragile signals. I will discuss the basics of information theory, compression, and compressive sensing. I will then discuss our recent work in compressive sensing. The topics of discussion include low-flux laser Radar, photonic phase transitions, high resolution biphoton ghost imaging, Ghost object tracking, 3D object tracking and high dimensional entanglement characterization. I will touch lightly on our current work of rapid wavefunction reconstruction and wavefront sensing. As an example (shown below), we were able efficiently and rapidly reconstruct high dimensional joint probability functions of biphotons in momentum and position. With conventional raster scanning this process would take approximately a year, but using double-pixel compressive sensing, the pictures were acquired in a few hours with modest flux.

Frontiers in Optics•Jan 1, 2014•0 citations
Quantum imaging based on entangled light sources exhibits enhanced background resistance compared to conventional imaging techniques in low-light conditions. However, direct imaging of dynamic targets remains challenging due to the limited count rate of entangled photons. In this paper, we propose a quantum imaging method based on quantum compressed sensing that leverages the strong correlation characteristics of entangled photons and the randomness inherent in photon pair generation and detection. This approach enables the construction of a compressed sensing system capable of directly imaging high-speed dynamic targets. The results demonstrate that our system successfully achieves imaging of a target rotating at a frequency of 10 kHz, while maintaining an impressive data compression rate of 10 −6 . This proposed method introduces a pioneering approach for the practical implementation of quantum imaging in real-world scenarios.
Compressive sensing utilizes sparsity to realize efficient image reconstruction. It is a valuable processing technique when cost, power, technology or computational overhead are limited or high. In the quantum domain technology usually limits efficient acquisition of weak or fragile signals. I will discuss the basics of information theory, compression, and compressive sensing. I will then discuss our recent work in compressive sensing. The topics of discussion include low-flux laser Radar, photonic phase transitions, high resolution biphoton ghost imaging, Ghost object tracking, 3D object tracking and high dimensional entanglement characterization. I will touch lightly on our current work of rapid wavefunction reconstruction and wavefront sensing. As an example (shown below), we were able efficiently and rapidly reconstruct high dimensional joint probability functions of biphotons in momentum and position. With conventional raster scanning this process would take approximately a year, but using double-pixel compressive sensing, the pictures were acquired in a few hours with modest flux.