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Plug-and-Play Quantum Adaptive Denoiser for Deconvolving Poisson Noisy Images

Abstract : 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, for example, 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.
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https://hal.archives-ouvertes.fr/hal-03276414
Contributor : Bertrand Georgeot Connect in order to contact the contributor
Submitted on : Friday, July 2, 2021 - 10:01:44 AM
Last modification on : Friday, October 22, 2021 - 4:20:10 PM

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Sayantan Dutta, Adrian Basarab, Bertrand Georgeot, Denis Kouamé. Plug-and-Play Quantum Adaptive Denoiser for Deconvolving Poisson Noisy Images. IEEE Access, IEEE, 2021, 9, pp.139771. ⟨10.1109/ACCESS.2021.3118608⟩. ⟨hal-03276414⟩

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