no code implementations • 6 Oct 2023 • Florent Sureau, Mahdi Latreche, Marion Savanier, Claude Comtat
In this work, we investigate hybrid PET reconstruction algorithms based on coupling a model-based variational reconstruction and the application of a separately learnt Deep Neural Network operator (DNN) in an ADMM Plug and Play framework.
1 code implementation • 12 Jun 2020 • Arnau Pujol, Jerome Bobin, Florent Sureau, Axel Guinot, Martin Kilbinger
The method estimates the individual shear responses of the objects from the combination of several measured properties on the images using supervised learning.
Cosmology and Nongalactic Astrophysics Instrumentation and Methods for Astrophysics
no code implementations • 1 Nov 2019 • Florent Sureau, Alexis Lechat, Jean-Luc Starck
Deconvolution of large survey images with millions of galaxies requires to develop a new generation of methods which can take into account a space variant Point Spread Function (PSF) and have to be at the same time accurate and fast.
no code implementations • 27 Jun 2018 • Arnau Pujol, Martin Kilbinger, Florent Sureau, Jerome Bobin
This shear response is the multiplicative shear bias for each image.
Cosmology and Nongalactic Astrophysics
no code implementations • 16 May 2017 • Joana Frontera-Pons, Florent Sureau, Jerome Bobin, Emeric Le Floc'h
In addition, preliminary results illustrate that this enables the capturing of extra physically meaningful information, such as redshift dependence, galaxy mass evolution and variation over the specific star formation rate.
Instrumentation and Methods for Astrophysics Astrophysics of Galaxies