45 citations · 92 across the 6 of their papers we have counts for
8 papers · 1 filter
Deep Unfolded Approximate Message Passing for Quantitative Acoustic Microscopy Image Reconstruction
Odysseas Pappas, Jonathan Mamou, Adrian Basarab +2
Quantitative Acoustic Microscopy (QAM) is an imaging technology utilising high frequency ultrasound to produce quantitative two-dimensional (2D) maps of acoustical and mechanical p…
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…
Fast High Resolution Blood Flow Estimation and Clutter Rejection via an Alternating Optimization Problem
Duong-Hung Pham, Adrian Basarab, Jean-Pierre Remenieras +2
This paper introduces a computationally efficient technique for estimating high-resolution Doppler blood flow from an ultrafast ultrasound image sequence. More precisely, it consis…
A Novel Fast 3D Single Image Super-Resolution Algorithm
Nwigbo Kenule Tuador, Duong Hung Pham, Jérôme Michetti +2
This paper introduces a novel computationally efficient method of solving the 3D single image super-resolution (SR) problem, i.e., reconstruction of a high-resolution volume from i…
Single Image Super-Resolution of Noisy 3D Dental CT Images Using Tucker Decomposition
J. Hatvani, A. Basarab, J. Michetti +2
Tensor decomposition has proven to be a strong tool in various 3D image processing tasks such as denoising and super-resolution. In this context, we recently proposed a canonical p…