An algorithm for non-convex off-the-grid sparse spike estimation with a minimum separation constraint - Archive ouverte HAL
Communication Dans Un Congrès Année : 2020

An algorithm for non-convex off-the-grid sparse spike estimation with a minimum separation constraint

Résumé

Theoretical results show that sparse off-the-grid spikes can be estimated from (possibly compressive) Fourier measurements under a minimum separation assumption. We propose a practical algorithm to minimize the corresponding non-convex functional based on a projected gradient descent coupled with an initialization procedure. We give qualitative insights on the theoretical foundations of the algorithm and provide experiments showing its potential for imaging problems.
Fichier principal
Vignette du fichier
proj_grad_itwist2020.pdf (590.15 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03037264 , version 1 (03-12-2020)

Identifiants

  • HAL Id : hal-03037264 , version 1

Citer

Yann Traonmilin, Jean-François Aujol, Arthur Leclaire. An algorithm for non-convex off-the-grid sparse spike estimation with a minimum separation constraint. in Proceedings of iTWIST'20, Paper-ID: 7, Nantes, France, December, 2-4, 2020, Dec 2020, Nantes, France. ⟨hal-03037264⟩

Collections

CNRS IMB INSMI
22 Consultations
33 Téléchargements

Partager

More