  A new Plug-and-Play (PnP) alternating direction of multipliers (ADMM) scheme
is proposed in this paper, by embedding a recently introduced adaptive denoiser
using the Schroedinger equation's solutions of quantum physics. The potential
of the proposed model is studied for Poisson image deconvolution, which is a
common problem occurring in number of imaging applications, such as limited
photon acquisition or X-ray computed tomography. Numerical results show the
efficiency and good adaptability of the proposed scheme compared to recent
state-of-the-art techniques, for both high and low signal-to-noise ratio
scenarios. This performance gain regardless of the amount of noise affecting
the observations is explained by the flexibility of the embedded quantum
denoiser constructed without anticipating any prior statistics about the noise,
which is one of the main advantages of this method. The main novelty of this
work resided in the integration of a modified quantum denoiser into the
PnP-ADMM framework and the numerical proof of convergence of the resulting
algorithm.
