activity
20182020
most citedSingle Image Super-Resolution of Noisy 3D Dental CT Images Using Tucker Decomposition

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

eess.IV20201 cited

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…

eess.IV2020

Joint Blind Deconvolution and Robust Principal Component Analysis for Blood Flow Estimation in Medical Ultrasound Imaging

Duong-Hung Pham, Adrian Basarab, Ilyess Zemmoura +2

This paper addresses the problem of high-resolution Doppler blood flow estimation from an ultrafast sequence of ultrasound images. Formulating the separation of clutter and blood c…

eess.IV2020

Outlier detection at the parcel-level in wheat and rapeseed crops using multispectral and SAR time series

Florian Mouret, Mohanad Albughdadi, Sylvie Duthoit +3

This paper studies the detection of anomalous crop development at the parcel-level based on an unsupervised outlier detection technique. The experimental validation is conducted on…

eess.IV2019

Preconditioned P-ULA for Joint Deconvolution-Segmentation of Ultrasound Images -- Extended Version

Corbineau Marie-Caroline, Kouamé Denis, Chouzenoux Emilie +2

Joint deconvolution and segmentation of ultrasound images is a challenging problem in medical imaging. By adopting a hierarchical Bayesian model, we propose an accelerated Markov c…

eess.SP2018

Adaptive transform via quantum signal processing: application to signal and image denoising

Raphaël Smith, Adrian Basarab, Bertrand Georgeot +1

The main scope of this paper is to show how tools from quantum mechanics, in particular the Schroedinger equation, can be used to construct an adaptive transform suitable for signa…