Quantum-enabled measurements for low light imaging

Arnab Chatterjee, Subrata Sarkar, Shreyas Changder +1 more

Abstract In recent years, multiple low light image enhancement algorithms have been developed, using both conventional techniques and machine learning based approaches. These techniques work as post processing methods, which add additional computational overhead. In this paper, a quantum image representation model has been proposed for low light images based on the Improved Simple Quantum Representation (ISQR). It is inspired by the Simple Quantum Representation (SQR) algorithm, which was originally designed for infrared imaging. ISQR extends its applicability by efficiently encoding low light grayscale and color images on quantum computing platforms As quantum imaging hardware is not yet commercially available, all experiments in this study were conducted through simulations to validate the proposed approach. ISQR is proposed as a quantum image representation technique in which classical pixel values are encoded into a quantum state , and an enhanced image is obtained after multiple quantum measurement and classical reconstruction. The enhancement performance of the proposed model is compared through multiple classical low light image enhancement algorithms and statistical analysis. In this paper, the coal mine and surveillance examples are shown primarily as qualitative case studies to demonstrate how ISQR behaves in extremely low light conditions. All these analyses and advantages highlight its potential for future quantum camera development.

Edoardo Charbon A

Hugo Defienne, Warwick P. Bowen, Maria V. Chekhova +5 more

Mu Zhou, Jiangli Peng, Jingyang Cao +2 more

Three-dimensional (3D) imaging in low-light environments has broad application prospects. High-quality 3D imaging requires obtaining both the depth and reflectivity information of the target. With the rapid development of Quantum Information Technology (QIT), Quantum Imaging (QI) provides a new approach to achieve high-quality 3D imaging. However, traditional QI methods are limited to Two-dimensional (2D) imaging and cannot accurately extract the depth information from the target. These methods also suffer from insufficient precision in reflectivity calculations. Therefore, we introduce a novel quantum 3D imaging and reflectivity estimation method based on entangled photons. Specifically, we first utilize the spatiotemporal correlation characteristics of entangled photon pairs combined with coincidence measurement technology to accurately determine target depth. Second, we analyze the distribution of entangled photon numbers during free-space transmission to construct a photon-based detection probability model. Third, we use this model to derive the probability density function of coincidence counts. Finally, we estimate the surface reflectivity information through statistical analysis of coincidence counting. Experimental results demonstrate that the proposed method can accurately reconstruct both depth and reflectivity profiles of the target in low-light environments. These findings validate the effectiveness of our method and highlight the potential of quantum 3D imaging for target detection in low-light environments.

Pratik J. Barge

Recent advances in quantum photonics promise transformative impacts on computing, communication, sensing, and imaging. This thesis explores two areas in photonic quantum technology: polarization entanglement dynamics in optical fibers and low-light imaging. Optical fibers are the most suitable medium for photonic qubits and long-distance entanglement distribution is a critical requirement to realize quantum technologies. We study the decay of polarization-entanglement of the Bell state photons propagating through imperfect optical fibers with spatially fluctuating refractive index. Furthermore, to extend the distribution distance, we propose the use of dynamical decoupling in the optical fiber using half waveplates and show that significant improvement in entanglement protection can be achieved even with sparsely spaced half waveplates along length of optical fiber. In the realm of imaging, traditional methods are often limited by noise, especially at low illumination levels necessary for certain applications. Quantum imaging techniques, utilizing non-classical light fields and spatial correlations, have demonstrated enhanced sensitivity. We demonstrate a novel imaging method based on spatial changes in the quadrature variance of an optical field, enabling effective imaging at extremely low light levels. Finally, we explore the use compressed sampling to minimize measurement requirements for image reconstruction in single-pixel imaging.

Paul‐Antoine Moreau, Ermes Toninelli, Thomas Gregory +1 more