34 citations · 85 across the 6 of their papers we have counts for
4 papers · 1 filter
DIVA: Deep Unfolded Network from Quantum Interactive Patches for Image Restoration
Sayantan Dutta, Adrian Basarab, Bertrand Georgeot +1
This paper presents a deep neural network called DIVA unfolding a baseline adaptive denoising algorithm (De-QuIP), relying on the theory of quantum many-body physics. Furthermore,…
A Novel Image Denoising Algorithm Using Concepts of Quantum Many-Body Theory
Sayantan Dutta, Adrian Basarab, Bertrand Georgeot +1
Sparse representation of real-life images is a very effective approach in imaging applications, such as denoising. In recent years, with the growth of computing power, data-driven…
Image Denoising Inspired by Quantum Many-Body physics
Sayantan Dutta, Adrian Basarab, Bertrand Georgeot +1
Decomposing an image through Fourier, DCT or wavelet transforms is still a common approach in digital image processing, in number of applications such as denoising. In this context…
Plug-and-Play Quantum Adaptive Denoiser for Deconvolving Poisson Noisy Images
Sayantan Dutta, Adrian Basarab, Bertrand Georgeot +1
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…