We apply the measurement reduction technique to optimally reconstruct an object image from multiplexed ghost images (GI) while taking into account both GI correlations and object image sparsity. We show that one can reconstruct an image in that way even if the object is illuminated by a small photon number. We consider frequency GI multiplexing using coupled parametric processes. We revealed that the imaging condition depends on the type of parametric process, namely, whether down- or up-conversion is used. Influence of information about sparsity in discrete cosine transform and Haar transform bases on reconstruction quality is studied. In addition, we compared ordinary and ghost images when the detectors are additionally illuminated by noise photons in a computer experiment, which showed increased noise immunity of GI, especially with processing via the proposed technique.
Quantum-enhanced ghost imaging recognition via joint optimization of speckle patterns and quantum network parameters
Nanjing University of Posts and Telecommunications（南京邮电大学）；Key Lab of Broadband Wireless Communication and Sensor Network Technology, Ministry of Education, Nanjing University of Posts and Telecommunications（南京邮电大学宽带无线通信与传感器网络技术教育部重点实验室）
Shanghai University（上海大学）；Inner Mongolia University of Technology（内蒙古工业大学）；KACST（沙特阿拉伯国王科学技术大学）；Institute of Quantum Technologies and Advanced Computing, KACST（沙特阿拉伯国王科学技术大学量子技术与先进计算研究所）
