This paper proposes a quantum-enhanced deep generative algorithm, Quantum Deep Generative Prior (QDGP), using programmable quantum circuits to generate quantum latent codes. The algorithm demonstrates superior reconstruction performance in optical ghost imaging experiments compared to classical methods, particularly at lower sampling rates. It also shows enhanced generalization capabilities in various computer vision tasks like image inpainting and colorization, exceeding the performance of classical counterparts.
